subject:(Image Processing Mathematical Models)

University of Florida

1. Chen, Qian. Image and Video Processing for Denoising, Coding, and Content Protection.

Degree: PhD, Electrical and Computer Engineering, 2011, University of Florida

► A typical digital video communication system consists of the following main parts: video capture, pre-processing, encoding, video security, video streaming over network, decoding and post-processing.… (more)

Subjects/Keywords: Data compression; Decryption; Estimate reliability; Image processing; Mathematical independent variables; Multilevel models; Parametric models; Pixels; Range searching; Video communications; coding – delay – model – video

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APA (6^th Edition):

Chen, Q. (2011). Image and Video Processing for Denoising, Coding, and Content Protection. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043648

Chicago Manual of Style (16^th Edition):

Chen, Qian. “Image and Video Processing for Denoising, Coding, and Content Protection.” 2011. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0043648.

MLA Handbook (7^th Edition):

Chen, Qian. “Image and Video Processing for Denoising, Coding, and Content Protection.” 2011. Web. 13 Dec 2019.

Vancouver:

Chen Q. Image and Video Processing for Denoising, Coding, and Content Protection. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0043648.

Council of Science Editors:

Chen Q. Image and Video Processing for Denoising, Coding, and Content Protection. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043648

University of Florida

2. Lee, Jun, 1957-. On speed-up procedures in ray tracing.

Degree: PhD, Electrical Engineering, 1994, University of Florida

URL: http://ufdc.ufl.edu/AA00039274

Subjects/Keywords: Algorithms; Binocular vision; Boxes; Copyrights; Eyes; Image processing; Images; Pixels; Ray tracing; Volume; Computer graphics – Mathematical models; Image processing – Digital techniques – Mathematical models

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APA (6^th Edition):

Lee, Jun, 1. (1994). On speed-up procedures in ray tracing. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039274

Chicago Manual of Style (16^th Edition):

Lee, Jun, 1957-. “On speed-up procedures in ray tracing.” 1994. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00039274.

MLA Handbook (7^th Edition):

Lee, Jun, 1957-. “On speed-up procedures in ray tracing.” 1994. Web. 13 Dec 2019.

Vancouver:

Lee, Jun 1. On speed-up procedures in ray tracing. [Internet] [Doctoral dissertation]. University of Florida; 1994. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00039274.

Council of Science Editors:

Lee, Jun 1. On speed-up procedures in ray tracing. [Doctoral Dissertation]. University of Florida; 1994. Available from: http://ufdc.ufl.edu/AA00039274

University of Florida

3. Zong, Xuli, 1960-. Sub-octave wavelet representations and applications for medical image processing.

Degree: PhD, Computer and Information Science and Engineering, 1997, University of Florida

URL: http://ufdc.ufl.edu/AA00013543

Subjects/Keywords: Algorithms; Data smoothing; Dyadics; Image contrast; Image enhancement; Image processing; Low noise; Noise reduction; Signals; Wavelet analysis; Image processing – Digital techniques – Mathematical models; Imaging systems in medicine – Mathematical models; Wavelets (Mathematics)

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APA (6^th Edition):

Zong, Xuli, 1. (1997). Sub-octave wavelet representations and applications for medical image processing. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00013543

Chicago Manual of Style (16^th Edition):

Zong, Xuli, 1960-. “Sub-octave wavelet representations and applications for medical image processing.” 1997. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00013543.

MLA Handbook (7^th Edition):

Zong, Xuli, 1960-. “Sub-octave wavelet representations and applications for medical image processing.” 1997. Web. 13 Dec 2019.

Vancouver:

Zong, Xuli 1. Sub-octave wavelet representations and applications for medical image processing. [Internet] [Doctoral dissertation]. University of Florida; 1997. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00013543.

Council of Science Editors:

Zong, Xuli 1. Sub-octave wavelet representations and applications for medical image processing. [Doctoral Dissertation]. University of Florida; 1997. Available from: http://ufdc.ufl.edu/AA00013543

University of Florida

4. Zapata, Iván R., 1975- ( Dissertant ). Detecting humans in video sequences using statistical color and shape models.

Degree: M.S, Electrical and Computer Engineering, 2001, University of Florida

URL: http://ufdc.ufl.edu/UF00100853

► We present a method for detecting and classifying humans and other objects from video images in a known environment. Specifically, we have developed and implemented… (more)

Subjects/Keywords: Basketball; Colors; Ellipses; Error rates; Image classification; Image processing; Mathematical vectors; Pixels; Skin; Statistical models; Computer vision; Image processing – Digital techniques; Optical pattern recognition

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APA (6^th Edition):

Zapata, Iván R., 1. (. D. ). (2001). Detecting humans in video sequences using statistical color and shape models. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UF00100853

Chicago Manual of Style (16^th Edition):

Zapata, Iván R., 1975- ( Dissertant ). “Detecting humans in video sequences using statistical color and shape models.” 2001. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UF00100853.

MLA Handbook (7^th Edition):

Zapata, Iván R., 1975- ( Dissertant ). “Detecting humans in video sequences using statistical color and shape models.” 2001. Web. 13 Dec 2019.

Vancouver:

Zapata, Iván R. 1(D). Detecting humans in video sequences using statistical color and shape models. [Internet] [Masters thesis]. University of Florida; 2001. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UF00100853.

Council of Science Editors:

Zapata, Iván R. 1(D). Detecting humans in video sequences using statistical color and shape models. [Masters Thesis]. University of Florida; 2001. Available from: http://ufdc.ufl.edu/UF00100853

University of Florida

5. Mandal, Chhandomay, 1972-. A dynamic framework for subdivision surfaces.

Degree: PhD, Computer and Information Science and Engineering, 1998, University of Florida

URL: http://ufdc.ufl.edu/AA00012984

Subjects/Keywords: Butterflies; Damping; Datasets; Degrees of freedom; Dynamic modeling; Geometric shapes; Matrices; Multilevel models; Topology; Vertices; Computer graphics – Mathematical models; Computer vision – Mathematical models; Image processing – Digital techniques

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APA (6^th Edition):

Mandal, Chhandomay, 1. (1998). A dynamic framework for subdivision surfaces. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00012984

Chicago Manual of Style (16^th Edition):

Mandal, Chhandomay, 1972-. “A dynamic framework for subdivision surfaces.” 1998. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00012984.

MLA Handbook (7^th Edition):

Mandal, Chhandomay, 1972-. “A dynamic framework for subdivision surfaces.” 1998. Web. 13 Dec 2019.

Vancouver:

Mandal, Chhandomay 1. A dynamic framework for subdivision surfaces. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00012984.

Council of Science Editors:

Mandal, Chhandomay 1. A dynamic framework for subdivision surfaces. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/AA00012984

University of Florida

6. Chandler, Rand Cole. Autonomous agent navigation based on textural analysis.

Degree: PhD, Electrical and Computer Engineering, 2003, University of Florida

URL: http://ufdc.ufl.edu/AA00039201

Subjects/Keywords: Algorithms; Image classification; Lawns; Mathematical vectors; Mowing; Pixels; Robots; Sidewalks; Signals; Wavelet analysis; Autonomous robots; Computer vision; Image processing – Mathematical models; Mobile agent systems

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APA (6^th Edition):

Chandler, R. C. (2003). Autonomous agent navigation based on textural analysis. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039201

Chicago Manual of Style (16^th Edition):

Chandler, Rand Cole. “Autonomous agent navigation based on textural analysis.” 2003. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00039201.

MLA Handbook (7^th Edition):

Chandler, Rand Cole. “Autonomous agent navigation based on textural analysis.” 2003. Web. 13 Dec 2019.

Vancouver:

Chandler RC. Autonomous agent navigation based on textural analysis. [Internet] [Doctoral dissertation]. University of Florida; 2003. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00039201.

Council of Science Editors:

Chandler RC. Autonomous agent navigation based on textural analysis. [Doctoral Dissertation]. University of Florida; 2003. Available from: http://ufdc.ufl.edu/AA00039201

University of Florida

7. Mandal, Chhandomay ( Dissertant ). Dynamic framework for subdivision surfaces.

Degree: PhD, Computer and Information Science and Engineering, 1998, University of Florida

URL: http://ufdc.ufl.edu/UF00101371

► Subdivision surfaces are extensively used to model smooth shapes of arbitrary topology. Recursive subdivision on a user-defined initial control mesh generates a visually pleasing smooth… (more)

▼ Subdivision surfaces are extensively used to model smooth shapes of arbitrary topology. Recursive subdivision on a user-defined initial control mesh generates a visually pleasing smooth surface in the limit. However, users have to carefully select the intiail mesh and.or manipulate the control vertex positions at different levels of subdivision hierarchy to satisfy the functional and aesthetic requirements in the smooth limit surface. This modeling drawback results fromt eh lack of direct manipulation tools for the limit surface. In this dissertation, techniques from physics-based modeling are integrated with geometric subdivision methodology, and a dynamic framework is presented for direct manipulation of the smooth limit surface generated by the subdivision schemes using physics based “force” tools. In a typical subdivision scheme, the user starts with an initial control mesh which is refined recursively using a fixed set of subdivision rules, and a smooth surface is produced in the limit. Most often this limit surface does not have an analytic expression, and hence poses challenging problems in incorporating mass and damping distribution functions, internal deformation energy, forces, and other physical quantities required to develop a physics-based subdivision surface model. In this dissertation, local parameterization techniques suitable for embedding the geometric subdivision surface model in a physics-based modeling framework have been developed. Specific local parameterization techniques have been fully developed for the Catmull-Clark, modified butterfly and the Loop subdivision schemes. Techniques for assigning material properties to geometric subdivision surfaces are derived, and a motion equation for the dynamic model has been formulated using Lagrangian dynamics. Furthermore, advantages of the physics-based deformable models are incorporated into the conventional subdivision schemes, and a dynamic hierarchical control of this model is introduced. Finally, a multiresolution representation of the control mesh is developed and a unified approach for deriving subdivision surface-based finite elements is presented. The proposed dynamic framework enhances the applicability of the subdivision surfaces in modeling applications. It is also useful for hierarchical shape recovery from large range and volume data sets, as well as for non-rigid motion tracking from a temporal sequence of data sets. Multiresolution representation of the initial mesh controlling the smooth limit surface enables global and local editing of the shape as desired by the modeler. This dynamic framework has also been used for synthesizing natural terrain models from sparse elevation data.

Subjects/Keywords: Butterflies; Damping; Data ranges; Datasets; Degrees of freedom; Dynamic modeling; Geometric shapes; Matrices; Topology; Vertices; Computer graphics – Mathematical models; Computer vision – Mathematical models; Image processing – Digital techniques

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Mandal, C. (. D. ). (1998). Dynamic framework for subdivision surfaces. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UF00101371

Chicago Manual of Style (16^th Edition):

Mandal, Chhandomay ( Dissertant ). “Dynamic framework for subdivision surfaces.” 1998. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UF00101371.

MLA Handbook (7^th Edition):

Mandal, Chhandomay ( Dissertant ). “Dynamic framework for subdivision surfaces.” 1998. Web. 13 Dec 2019.

Vancouver:

Mandal C(D). Dynamic framework for subdivision surfaces. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UF00101371.

Council of Science Editors:

Mandal C(D). Dynamic framework for subdivision surfaces. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/UF00101371

University of Florida

8. Posirca, Iulia M. Variational Models for Simultaneous Image Segmentation and Noise Removal.

Degree: PhD, Mathematics, 2012, University of Florida

URL: http://ufdc.ufl.edu/UFE0044953

► We present two projects for simultaneous image segmentation and noise removal. The first project concerns the images corrupted with Gaussian noise and the second one… (more)

Subjects/Keywords: Data smoothing; Image processing; Image reconstruction; Imaging; Mathematics; Modeling; Pixels; Statistical models; Supernova remnants; Ultrasonography; image – noise – segmentation – variational

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APA (6^th Edition):

Posirca, I. M. (2012). Variational Models for Simultaneous Image Segmentation and Noise Removal. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044953

Chicago Manual of Style (16^th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0044953.

MLA Handbook (7^th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Web. 13 Dec 2019.

Vancouver:

Posirca IM. Variational Models for Simultaneous Image Segmentation and Noise Removal. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0044953.

Council of Science Editors:

Posirca IM. Variational Models for Simultaneous Image Segmentation and Noise Removal. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044953

University of Florida

9. Chang, Ji-Ho. Image reconstruction algorithms for achieving high-resolution positron emission tomography images.

Degree: PhD, Electrical and Computer Engineering, 2004, University of Florida

URL: http://ufdc.ufl.edu/AA00039579

Subjects/Keywords: Algorithms; Image contrast; Image reconstruction; Matrices; Objective functions; Penalty function; Pets; Photons; Standard deviation; Tumors; Image processing – Digital techniques; Imaging systems in medicine – Mathematical models; Tomography, Emission

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chang, J. (2004). Image reconstruction algorithms for achieving high-resolution positron emission tomography images. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039579

Chicago Manual of Style (16^th Edition):

Chang, Ji-Ho. “Image reconstruction algorithms for achieving high-resolution positron emission tomography images.” 2004. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00039579.

MLA Handbook (7^th Edition):

Chang, Ji-Ho. “Image reconstruction algorithms for achieving high-resolution positron emission tomography images.” 2004. Web. 13 Dec 2019.

Vancouver:

Chang J. Image reconstruction algorithms for achieving high-resolution positron emission tomography images. [Internet] [Doctoral dissertation]. University of Florida; 2004. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00039579.

Council of Science Editors:

Chang J. Image reconstruction algorithms for achieving high-resolution positron emission tomography images. [Doctoral Dissertation]. University of Florida; 2004. Available from: http://ufdc.ufl.edu/AA00039579

University of Florida

10. Guo, Yanlin, 1971-. Snake pedals : active geometric models for shape modeling and recovery.

Degree: PhD, Electrical and Computer Engineering, 1998, University of Florida

URL: http://ufdc.ufl.edu/AA00034778

Subjects/Keywords: Coordinate systems; Curvature; Ellipses; Geometric shapes; Parametric models; Pedal points; Snakes; Stiffness matrix; Three dimensional modeling; Topology; Computer vision – Mathematical models ( fast ); Image processing – Digital techniques ( fast )

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Guo, Yanlin, 1. (1998). Snake pedals : active geometric models for shape modeling and recovery. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00034778

Chicago Manual of Style (16^th Edition):

Guo, Yanlin, 1971-. “Snake pedals : active geometric models for shape modeling and recovery.” 1998. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00034778.

MLA Handbook (7^th Edition):

Guo, Yanlin, 1971-. “Snake pedals : active geometric models for shape modeling and recovery.” 1998. Web. 13 Dec 2019.

Vancouver:

Guo, Yanlin 1. Snake pedals : active geometric models for shape modeling and recovery. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00034778.

Council of Science Editors:

Guo, Yanlin 1. Snake pedals : active geometric models for shape modeling and recovery. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/AA00034778

University of Florida

11. Lee, Wen-Hsiung. Maximum likelihood estimation of detector efficiencies in positron emission tomography.

Degree: PhD, Electrical and Computer Engineering, 2001, University of Florida

URL: http://ufdc.ufl.edu/AA00039257

Subjects/Keywords: Data models; Estimation methods; Fisher information; Geometric angles; Image reconstruction; Pets; Photons; Positrons; Random variables; Simulations; Image processing – Digital techniques; Imaging systems in medicine – Mathematical models; Tomography, Emission

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lee, W. (2001). Maximum likelihood estimation of detector efficiencies in positron emission tomography. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039257

Chicago Manual of Style (16^th Edition):

Lee, Wen-Hsiung. “Maximum likelihood estimation of detector efficiencies in positron emission tomography.” 2001. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00039257.

MLA Handbook (7^th Edition):

Lee, Wen-Hsiung. “Maximum likelihood estimation of detector efficiencies in positron emission tomography.” 2001. Web. 13 Dec 2019.

Vancouver:

Lee W. Maximum likelihood estimation of detector efficiencies in positron emission tomography. [Internet] [Doctoral dissertation]. University of Florida; 2001. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00039257.

Council of Science Editors:

Lee W. Maximum likelihood estimation of detector efficiencies in positron emission tomography. [Doctoral Dissertation]. University of Florida; 2001. Available from: http://ufdc.ufl.edu/AA00039257

University of Florida

12. Malladi, Ravikanth, 1966. A topology-independent shape modeling scheme.

Degree: 1993, University of Florida

URL: http://ufdc.ufl.edu/AA00039158

Subjects/Keywords: Approximation; Computer vision; Curvature; Equations of motion; Geometric shapes; Modeling; Snakes; Surface contours; Three dimensional modeling; Topology; Computer and Information Sciences thesis Ph. D; Computer vision – Mathematical models; Image processing – Mathematical models

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APA (6^th Edition):

Malladi, Ravikanth, 1. (1993). A topology-independent shape modeling scheme. (Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039158

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Malladi, Ravikanth, 1966. “A topology-independent shape modeling scheme.” 1993. Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00039158.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Malladi, Ravikanth, 1966. “A topology-independent shape modeling scheme.” 1993. Web. 13 Dec 2019.

Vancouver:

Malladi, Ravikanth 1. A topology-independent shape modeling scheme. [Internet] [Thesis]. University of Florida; 1993. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00039158.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Malladi, Ravikanth 1. A topology-independent shape modeling scheme. [Thesis]. University of Florida; 1993. Available from: http://ufdc.ufl.edu/AA00039158

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Florida

13. Chen, Fuhua. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.

Degree: PhD, Mathematics, 2012, University of Florida

URL: http://ufdc.ufl.edu/UFE0044393

► Image segmentation is the first stage of image processing and analysis. The result of image segmentation is used for image post-processing. In computer vision, segmentation… (more)

Subjects/Keywords: Algorithms; Approximation; Computer vision; Gaussian distributions; Gray matter; Image processing; Membership functions; Pixels; Stochastic models; White matter; image – multiphase – processing – segmentation – supervised

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chen, F. (2012). Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044393

Chicago Manual of Style (16^th Edition):

Chen, Fuhua. “Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.” 2012. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0044393.

MLA Handbook (7^th Edition):

Chen, Fuhua. “Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications.” 2012. Web. 13 Dec 2019.

Vancouver:

Chen F. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0044393.

Council of Science Editors:

Chen F. Multiphase Image Segmentation Based on Intensity Statistics Modeling and Applications. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044393

University of Florida

14. Lee, Jin-Seop. Image registration by using statistical information.

Degree: PhD, Mathematics, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0045405

► Image registration has been an important subject in many areas including remote sensing, computer vision, and medical imaging. It has been intensively studied and many… (more)

▼ Image registration has been an important subject in many areas including remote sensing, computer vision, and medical imaging. It has been intensively studied and many registration techniques have been developed. This dissertation focuses on the development of inverse consistent non-rigid image registration which are used, especially, in medical image area. In this dissertation, we first propose a novel variational model for mono-modal non-rigid image registration. This model uses a similarity measure derived from the maximum likelihood estimation of the residual with different local variances. By automatically updated different local variances at each iteration, the choice of the weight parameter balancing the regularization term and the similarity measure term becomes more flexible, and the accuracy and robustness are also improved. Secondly, we propose a new variational model for multi-modal non-rigid image registration, where the similarity measure is derived from R´enyi’s statistical dependence measure. By using this measure, the difficulty of estimation of the joint pdf, which is required in the mutual information based registration, can be avoided. Furthermore, the computation is simplified by using the theory of reproducing kernel Hilbert space. Thirdly, we propose a new variational model for inverse consistent non-rigid image registration. This model computes the forward and backward transformations that deform the source image to match the target image and vice versa, by minimizing a energy function that consists of the regularization term of the deformation fields, the error term of the alignment, and the inverse inconsistency cost term. By applying the inverse consistent registration, measurements or segmentations on one image can be precisely transferred to the other, which is especially important for medical treatment such as image-guided radiation therapy and surgery. Lastly, we propose a new variational model for bidirectional inverse consistent multi-modal non-rigid image registration. That model deforms the source image and the target image simultaneously and minimizes the disparity between the deformed source image and the deformed target image. This method can handle relatively larger deformation and is good for parallel computing. ( en ) Advisors/Committee Members: Chen, Yunmei (committee chair), Zhang, Lei (committee member), Rao, Murali (committee member), Shen, Li C (committee member), Ge, Jian (committee member).

Subjects/Keywords: Computerized axial tomography; Coordinate transformations; Correlation coefficients; Diagnostic imaging; Image processing; Images; Images of transformations; Lungs; Parametric models; Statistical models; aos – image – information – measure

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APA (6^th Edition):

Lee, J. (2013). Image registration by using statistical information. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045405

Chicago Manual of Style (16^th Edition):

Lee, Jin-Seop. “Image registration by using statistical information.” 2013. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0045405.

MLA Handbook (7^th Edition):

Lee, Jin-Seop. “Image registration by using statistical information.” 2013. Web. 13 Dec 2019.

Vancouver:

Lee J. Image registration by using statistical information. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0045405.

Council of Science Editors:

Lee J. Image registration by using statistical information. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045405

University of Florida

15. Shi, Jiangli. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.

Degree: PhD, Mathematics, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0045845

► A series of mathematical models for image registrations are investigated in this work to provide a variety of techniques especially for medical image alignment. Analysis… (more)

▼ A series of mathematical models for image registrations are investigated in this work to provide a variety of techniques especially for medical image alignment. Analysis of robustness, efficiency and accuracy for each model is included in order to give comparisons and therefore to show advantages and limitations for each model. As shown in this thesis matching similar structures between several image modalities poses extreme difficulties for images with complex structures. Those difficulties primarily stem from the nonlinear relation and unknown quantization effects of intensity values. However, potential of a large variety of industrial applications makes it inevitable to register similar structures between several image modalities, for which direct intensity comparison is not possible. In particular, in the applications of medical imaging, images with different modalities often need to be registered for an accurate fusion of complementary information. To tackle with those difficulties, we introduced a statistical dependence measure into multi-model image registration. A novel variational model for deformable multi-modal image registration is then proposed. As an alternative to the models based on maximizing mutual information, the Renyi’s statistical dependence measure of two random variables is proposed as a measure of the goodness of matching in our objective functional. The proposed model does not require an estimation of the continuous joint probability density function. Instead, it only needs observed independent samples. Moreover, the theory of reproducing kernel Hilbert spaces is used to simplify the computation. Experimental results with comparisons are provided to show the effectiveness of the proposed model. Finally we introduced a registration assisted non-parametric segmentation model as an application of Renyi’s statistical dependence measure. This model generates a label image , which represents the location of the edges separating the homogeneous regions in the given image, by assigning different constants on each of the sub-regions. Registration is then applied to the image to be segmented and the generated label image. This is accomplished by maximizing the similarity between those two images. As the label image is deformed from the process of registration, the location of the edges in the label image gradually moves to the same location of the edges in the segmenting image. Finally, the best alignment of those two images provides a best segmentation result, rendering a suitable choice of similarity measure extremely important for this problem. Since those two images are no longer of the same modalities, the direct comparison of their intensities fails. By using Rényi's statistical dependence measure the proposed model deals directly with independent samples and does not need to estimate the continuous joint probability density function, which is time consuming. Furthermore, the computation is greatly simplified by using the theory of reproducing kernel Hilbert spaces. Experimental results for… Advisors/Committee Members: Chen, Yunmei (committee chair), Rao, Murali (committee member), Shen, Li C (committee member), Mccullough, Scott A (committee member), Gilland, David R (committee member).

Subjects/Keywords: Coordinate transformations; Cross correlation; Entropy; Image processing; Images of transformations; Linear transformations; Parametric models; Random variables; Sine function; Statistical models; dependence – image – measure – registration – segmentation – statistical

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APA (6^th Edition):

Shi, J. (2013). Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045845

Chicago Manual of Style (16^th Edition):

Shi, Jiangli. “Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.” 2013. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0045845.

MLA Handbook (7^th Edition):

Shi, Jiangli. “Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation.” 2013. Web. 13 Dec 2019.

Vancouver:

Shi J. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0045845.

Council of Science Editors:

Shi J. Statistical Dependence Measure Based Multi-Model Image Registration and Registration Assisted Non-Parametric Image Segmentation. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045845

University of Florida

16. Beharry, Kara. Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System.

Degree: MS, Nuclear Engineering Sciences - Nuclear and Radiological Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0025146

► The University of Florida Backscatter X-ray (BSX) Imaging system has played an integral role for industries that employ non-destructive testing on equipment and target samples… (more)

▼ The University of Florida Backscatter X-ray (BSX) Imaging system has played an integral role for industries that employ non-destructive testing on equipment and target samples of varying materials. A BSX system provides the ability to image a target from the same side as the x-ray illumination. Due to its unique image acquisition capabilities, various simulations and experiments are continuously being conducted at the University of Florida in order to refine and improve the system and the system?s efficiency in order to fulfill the requirements that industry expects from it. In almost all detector systems there are limitations and the UF BSX imaging system it is no different. Experiments have been performed to analyze the image contrast of detectors in integrating mode, to examine image quality at high count rates, and to estimate the system dead time. Use of the integrating mode has shown that contrast improves for deep void defects in foam (Spray on Foam Insulation) without adversely affecting the contrast of shallow void defects. Analysis of the UF BSX imaging system has demonstrated that it follows a paralyzable model and because of this paralyzable behavior inversion of image contrast occurs at high count rates. Furthermore, based on the paralyzable model estimations of the system dead time (tau) was evaluated. The system dead time (tau) depended on material choice, detector type and position. For the Sodium-Iodide (NaI) detectors, values of tau were calculated that fell within the range of 5.27x10-07 s < tau NaI Series < 5.47x10-07 s. For the YSO detectors, two ranges are given corresponding to the tau values before the reset of the baseline restore constant and after the reset of the baseline restore constant respectively, 3.53x10-07 s < tau YSO Series < 3.79x10-07 s and 1.64x10-07 s < tau YSO Series < 1.95x10-07 s. Throughout the experiments it was observed that the maximum predicted count rate limit of 2.00x10+06 (cps) for the YSO detector was not being achieved. This behavior led to separate testing of the individual components that constitute the BSX system. Currently the reason for the YSO count rate limitation has not been definitively determined, but the problem is believed to be in the pre-amplifier. Additional testing and analysis needs to be performed. ( en ) Advisors/Committee Members: Dugan, Edward T. (committee chair), Baciak, James (committee member).

Subjects/Keywords: Dead time; Diameters; Electric potential; Foams; Image contrast; Image filters; Image processing; Photographs; Solar X rays; Time series models; backscatter, contrast, paralyzable

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Beharry, K. (2009). Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0025146

Chicago Manual of Style (16^th Edition):

Beharry, Kara. “Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System.” 2009. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0025146.

MLA Handbook (7^th Edition):

Beharry, Kara. “Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System.” 2009. Web. 13 Dec 2019.

Vancouver:

Beharry K. Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System. [Internet] [Masters thesis]. University of Florida; 2009. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0025146.

Council of Science Editors:

Beharry K. Image Contrast and Quality Studies and System Dead-Time Studies for the University of Florida Backscatter X-Ray Imaging System. [Masters Thesis]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0025146

University of Florida

17. Wu, Chen-Hsien. Attenuation correction methods for positron emission tomography.

Degree: PhD, Electrical and Computer Engineering, 1998, University of Florida

URL: http://ufdc.ufl.edu/AA00021354

Subjects/Keywords: Algorithms; Density estimation; Diagnostic imaging; Estimation methods; Image reconstruction; Lungs; Maximum likelihood estimations; Pets; Photons; Transcriptional regulatory elements; Image processing – Digital techniques; Imaging systems in medicine – Mathematical models; Tomography, Emission

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APA (6^th Edition):

Wu, C. (1998). Attenuation correction methods for positron emission tomography. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00021354

Chicago Manual of Style (16^th Edition):

Wu, Chen-Hsien. “Attenuation correction methods for positron emission tomography.” 1998. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00021354.

MLA Handbook (7^th Edition):

Wu, Chen-Hsien. “Attenuation correction methods for positron emission tomography.” 1998. Web. 13 Dec 2019.

Vancouver:

Wu C. Attenuation correction methods for positron emission tomography. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00021354.

Council of Science Editors:

Wu C. Attenuation correction methods for positron emission tomography. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/AA00021354

University of Florida

18. Niu,Angela. Camera Based Robotic Control.

Degree: MS, Mechanical Engineering - Mechanical and Aerospace Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043417

► Computer vision is a new field of study that can greatly be used in autonomous vehicle navigation or other industrial automation. In this thesis, the… (more)

Subjects/Keywords: Computer vision; Coordinate transformations; Homography; Image processing; Image rotation; Images of transformations; Object recognition; Parametric models; Principal components analysis; Subject terms; recognition – sift – stitching

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APA (6^th Edition):

Niu,Angela. (2011). Camera Based Robotic Control. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043417

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

Niu,Angela. “Camera Based Robotic Control.” 2011. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0043417.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

Niu,Angela. “Camera Based Robotic Control.” 2011. Web. 13 Dec 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Niu,Angela. Camera Based Robotic Control. [Internet] [Masters thesis]. University of Florida; 2011. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0043417.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Niu,Angela. Camera Based Robotic Control. [Masters Thesis]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043417

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Florida

19. Subakan, Ozlem. Continuous Mixture Models for Feature Preserving Smoothing and Segmentation.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0024915

► Image smoothing and segmentation are fundamental tasks in computer vision. Although there are numerous algorithms that have been developed and applied to these tasks in… (more)

▼ Image smoothing and segmentation are fundamental tasks in computer vision. Although there are numerous algorithms that have been developed and applied to these tasks in various application domains, several challenges remain unconquered. In this dissertation, we consider the challenge of achieving smoothing and segmentation while preserving complicated and detailed features present in the image, be it a gray level or a color image. We present novel approaches that do not make use of any prior information about the objects in the image being processed, and yet produce promising results. The key idea here is to model the derived local orientation information via a continuous mixture of appropriate basis functions. We present several such models considering grayscale and color images separately. We propose two models for grayscale images; one involving a continuous mixture over the covariance matrices of Gaussian basis functions, and another involving a continuous mixture over the mean direction vectors of Watson basis functions. For color image processing, we introduce a novel Quaternionic Gabor Filter (QGF) which can combine the color channels and the orientations in the image plane. The local orientation information in the color images can be extracted using the QGFs. We show that these filters are optimally localized both in the spatial and frequency domains and provide a good approximation to quaternionic quadrature filters. In a second logical step, we propose continuous mixtures of appropriate hypercomplex exponential basis functions to model this local orientation information. We derive closed form solutions for the proposed models. These continuous mixture models are then used to construct spatially varying kernels which are convolved with the color image or the signed distance function of an evolving contour (placed in the color image) to achieve feature preserving smoothing or segmentation, respectively. We compare and quantitatively validate the proposed models with numerous experimental results on real images including the images drawn from Berkeley Segmentation Data Set. These comparisons revealed that the techniques we developed are superior than the state-of-the-art algorithms described in the literature. Finally, the dissertation is concluded with a list of potential directions for future research. ( en ) Advisors/Committee Members: Vemuri, Baba C. (committee chair), Rangarajan, Anand (committee member), Ho, Jeffrey (committee member), Banerjee, Arunava (committee member), Vallejos, Carlos E. (committee member).

Subjects/Keywords: Computer vision; Curvature; Data smoothing; Gabor filters; Image enhancement; Image filters; Image processing; Images; Matrices; Quaternions; bingham, color, continuous, directional, distributions, filters, fisher, gabor, gaussian, image, mixture, models, quaternions, segmentation, smoothing, watson, wishart

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Subakan, O. (2009). Continuous Mixture Models for Feature Preserving Smoothing and Segmentation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0024915

Chicago Manual of Style (16^th Edition):

Subakan, Ozlem. “Continuous Mixture Models for Feature Preserving Smoothing and Segmentation.” 2009. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0024915.

MLA Handbook (7^th Edition):

Subakan, Ozlem. “Continuous Mixture Models for Feature Preserving Smoothing and Segmentation.” 2009. Web. 13 Dec 2019.

Vancouver:

Subakan O. Continuous Mixture Models for Feature Preserving Smoothing and Segmentation. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0024915.

Council of Science Editors:

Subakan O. Continuous Mixture Models for Feature Preserving Smoothing and Segmentation. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0024915

University of Florida

20. Wang, Ludong, 1961-. Local dynamic modeling with self-organizing feature maps.

Degree: PhD, Electrical and Computer Engineering, 1996, University of Florida

URL: http://ufdc.ufl.edu/AA00032516

Subjects/Keywords: Architectural models; Dynamic modeling; Learning; Linear models; Mathematical vectors; Modeling; Neurons; Signals; Time series; Time series models; Chaotic behavior in systems; Dynamics – Mathematical models; Self-organizing systems – Data processing; Signal processing – Mathematical models

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, Ludong, 1. (1996). Local dynamic modeling with self-organizing feature maps. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00032516

Chicago Manual of Style (16^th Edition):

Wang, Ludong, 1961-. “Local dynamic modeling with self-organizing feature maps.” 1996. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00032516.

MLA Handbook (7^th Edition):

Wang, Ludong, 1961-. “Local dynamic modeling with self-organizing feature maps.” 1996. Web. 13 Dec 2019.

Vancouver:

Wang, Ludong 1. Local dynamic modeling with self-organizing feature maps. [Internet] [Doctoral dissertation]. University of Florida; 1996. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00032516.

Council of Science Editors:

Wang, Ludong 1. Local dynamic modeling with self-organizing feature maps. [Doctoral Dissertation]. University of Florida; 1996. Available from: http://ufdc.ufl.edu/AA00032516

University of Florida

21. Wang, Chih-Fang, 1967-. Algorithms for the Otis optoelectronic computer.

Degree: PhD, Computer and Information Science and Engineering, 1998, University of Florida

URL: http://ufdc.ufl.edu/AA00034762

Subjects/Keywords: Algorithms; Broadcasting industry; Electronics; Histograms; Image processing; Mathematical vectors; Matrices; Permutations; Pixels; Simulations

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, Chih-Fang, 1. (1998). Algorithms for the Otis optoelectronic computer. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00034762

Chicago Manual of Style (16^th Edition):

Wang, Chih-Fang, 1967-. “Algorithms for the Otis optoelectronic computer.” 1998. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00034762.

MLA Handbook (7^th Edition):

Wang, Chih-Fang, 1967-. “Algorithms for the Otis optoelectronic computer.” 1998. Web. 13 Dec 2019.

Vancouver:

Wang, Chih-Fang 1. Algorithms for the Otis optoelectronic computer. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00034762.

Council of Science Editors:

Wang, Chih-Fang 1. Algorithms for the Otis optoelectronic computer. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/AA00034762

University of Florida

22. Sussner, Peter. Matrix decomposition in minimax algebra and applications in image processing.

Degree: PhD, Mathematics, 1996, University of Florida

URL: http://ufdc.ufl.edu/AA00034601

Subjects/Keywords: Algebra; Algorithms; Approximation; Image processing; Integers; Linear algebra; Mathematical vectors; Mathematics; Matrices; Minimax

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sussner, P. (1996). Matrix decomposition in minimax algebra and applications in image processing. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00034601

Chicago Manual of Style (16^th Edition):

Sussner, Peter. “Matrix decomposition in minimax algebra and applications in image processing.” 1996. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00034601.

MLA Handbook (7^th Edition):

Sussner, Peter. “Matrix decomposition in minimax algebra and applications in image processing.” 1996. Web. 13 Dec 2019.

Vancouver:

Sussner P. Matrix decomposition in minimax algebra and applications in image processing. [Internet] [Doctoral dissertation]. University of Florida; 1996. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00034601.

Council of Science Editors:

Sussner P. Matrix decomposition in minimax algebra and applications in image processing. [Doctoral Dissertation]. University of Florida; 1996. Available from: http://ufdc.ufl.edu/AA00034601

University of Florida

23. Zhang, Haili. Mathematical Modeling for Image Segmentation and Restoration.

Degree: PhD, Mathematics, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0045847

► This thesis is devoted to the formulation, implementation, and improvement of mathematical models and efficient algorithms for image segmentation and image restoration using tools based… (more)

▼ This thesis is devoted to the formulation, implementation, and improvement of mathematical models and efficient algorithms for image segmentation and image restoration using tools based on partial differential equation (PDE), calculus of variations, numerical optimizations, and statistical methods. Image segmentation or pattern classification is to partition image domain into disjointed subregions such that each region corresponds to a single subject. This problem is of fundamental importance in digital image processing and has wide applications. During the last few decades, a considerable amount of approaches have emerged to tackle this issue. However, the difficulties caused by intensity inhomogeneity, higher level of noise, and unevenly distributed illumination still need to be addressed. In this thesis, we propose two main results: a nonparametric image segmentation model based Renyi's statistical dependence measure and a fast algorithm for multiphase image segmentation with bias correction. Our second focus is image restoration. Due to limitations of hardware or erroneous transmission, images we obtain in real world may contain certain kind of distortion and noise. The goal of image restoration is to recover the latent clear image from observed contaminated data. The fields of image restoration is very broad, and it is impossible to cover all the related fields. In this thesis, we only deal with joint image deblurring and denoising. This is in general an ill-posed problem, and certain regularization technique must be imposed. In this work, we choose to use sparse representation theory, and propose a sparseland model for deblurring images in the presence of impulse noise. The main results of this thesis are summarized as the following: 1. Nonparametric Image Segmentation Using Rényi's Statistical Dependence Measure In this thesis, we present a novel nonparametric active region model for image segmentation. This model partitions an image by maximizing the similarity between the image and a label image, which is generated by setting different constants as the intensities of partitioned subregions. The intensities of these two images cannot be directly compared as they are of different modalities. In this work, we use Rényi's statistical dependence measure, maximum cross correlation, as a criterion to measure their similarity. By using this measure, the proposed model deals directly with independent samples and does not need to estimate the continuous joint probability density function. Moreover, the computation is further simplified by applying the theory of reproducing kernel Hilbert spaces. Experimental results based on medical and synthetic images are provided to demonstrate the effectiveness of the proposed method. 2. An Efficient Algorithm for Multiphase Image Segmentation with Intensity Bias Correction In addition, we propose a variational model for simultaneous multiphase segmentation and intensity bias estimation for images corrupted by strong noise and intensity inhomogeneity. Since the… Advisors/Committee Members: Chen, Yunmei (committee chair), Zhang, Lei (committee member), Rao, Murali (committee member), Mccullough, Scott A (committee member), White, Keith D (committee member).

Subjects/Keywords: Algorithms; Eigenfunctions; Gray matter; Histograms; Image processing; Images of transformations; Inhomogeneity; Noise intensity; Parametric models; Pixels; algorithm – deblurring – denoising – nonparametric – restoration – segmentation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhang, H. (2013). Mathematical Modeling for Image Segmentation and Restoration. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045847

Chicago Manual of Style (16^th Edition):

Zhang, Haili. “Mathematical Modeling for Image Segmentation and Restoration.” 2013. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0045847.

MLA Handbook (7^th Edition):

Zhang, Haili. “Mathematical Modeling for Image Segmentation and Restoration.” 2013. Web. 13 Dec 2019.

Vancouver:

Zhang H. Mathematical Modeling for Image Segmentation and Restoration. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0045847.

Council of Science Editors:

Zhang H. Mathematical Modeling for Image Segmentation and Restoration. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045847

University of Florida

24. Paluri, Sravanti. Modeling Headspace Pressure in Retortable Packages.

Degree: MS, Chemical Engineering, 2012, University of Florida

URL: http://ufdc.ufl.edu/UFE0045117

► Flexible packages, a new attraction in the market for shelf-stable canned foods, are more susceptible to damage during thermal processing for sterilization. In order to… (more)

▼ Flexible packages, a new attraction in the market for shelf-stable canned foods, are more susceptible to damage during thermal processing for sterilization. In order to maintain the integrity of the package, it is important to keep the pressure differential across the package walls at a minimum. In this study,experiments were carried out to predict internal pressure in the headspace of a rigid pressure-tight module that withstood variations in temperatures and pressures. A stainless steel module was custom-made with a reseal-able lid,provisions for thermocouples, an inlet valve from which to pull vacuum, and a dial gauge to measure headspace pressure. The module was instrumented so as to measure and record the temperature profile at two different locations, one near the top and one near the bottom of the module, while undergoing thermal processing in a retort. For each set of experiments, three food systems were used to fill the module; pure distilled water, saline solution (5%) and sucrose solution (10%). A mathematical model was used to predict the headspace pressure profile in response to two experimentally measured temperature profiles (near the top and bottom). Results from these studies were compared with results from earlier work to account for the error between experimental and predicted headspace pressure profiles found in that work. This will lead to better control and knowledge of over pressures required during thermal processing to minimize differential pressure, thus avoiding damage to the flexible packaging and maintaining the quality and safety of food. Results showed that differences between predicted pressures from top and bottom temperatures and differences between measured and predicted pressures found in the previous work followed similar patterns and were of the same order of magnitude. These findings supported the hypothesis that disagreement between measured and predicted pressures found in the previous work was likely due to the reason that the temperatures used to predict pressures were measured at the bottom of the module, while the measured pressure was generated in response to headspace temperature at the top of the module. ( en ) Advisors/Committee Members: Svoronos, Spyros (committee chair), Welt, Bruce A (committee member).

Subjects/Keywords: Internal pressure; Mathematical models; Modeling; Pressure; Steam; Temperature profiles; Thermocouples; Vacuum; Water distillation; Water temperature; canned – flexible – headspace – modeling – package – pressure – processing – thermal

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APA (6^th Edition):

Paluri, S. (2012). Modeling Headspace Pressure in Retortable Packages. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045117

Chicago Manual of Style (16^th Edition):

Paluri, Sravanti. “Modeling Headspace Pressure in Retortable Packages.” 2012. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0045117.

MLA Handbook (7^th Edition):

Paluri, Sravanti. “Modeling Headspace Pressure in Retortable Packages.” 2012. Web. 13 Dec 2019.

Vancouver:

Paluri S. Modeling Headspace Pressure in Retortable Packages. [Internet] [Masters thesis]. University of Florida; 2012. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0045117.

Council of Science Editors:

Paluri S. Modeling Headspace Pressure in Retortable Packages. [Masters Thesis]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0045117

University of Florida

25. Celebi, Samel, 1966- ( Dissertant ). Representation of locally stationary signals using lowpass moments.

Degree: PhD, Electrical and Computer Engineering, 1995, University of Florida

URL: http://ufdc.ufl.edu/UF00082352

► The gamma filter is a generalized feedforward structure which can implemented as a cascade of identical first order lowpass filters. Although functionally it is an… (more)

▼ The gamma filter is a generalized feedforward structure which can implemented as a cascade of identical first order lowpass filters. Although functionally it is an infinite impulse response (IIR) filter, topologically it mimics a finite impulse response (FIR) filter. As a result of this blend, it inherits the computational power of the former and the easy stability analysis of the latter. Being a single input multiple output structure, the gamma filter is characterized by its order and the time scale which linearly warps the time axis. Furthermore, when orthogonalized, the gamma filter transforms into the well-known Laguerre filter. The gamma kernels correspond to the impulse responses of the gamma filter outputs. This family of decaying exponentials form a complete set in the Hilbert space. The first problem attacked in this study is the approximation of a given signal as a weighted sum of gamma kernels such that the mean square error is minimized. conditions for the optimum weights and time scale are derived and they are decoupled from each other. A vector space interpretation of the role of the time scale is also provided. According to this interpretation the time scale parameter has the effect of changing the relative angle between the desired signal and the gamma projection space without altering the structure of the gamma space. Two numerical methods to estimate the time scale are included. The gamma filter produces at its tap, the Poisson moments of the input signal. Poisson moments correspond to the Taylor's series coefficients of the recent magnitude spectrum of the input signal at zero frequency. Localized in time and frequency, Poisson moments offer a computationally inexpensive, alternate time-frequency representation for locally stationary signals, such as speech. In the analog domain the moments can be physically measured and fed into a nonlinear mapper, such as an artificial neural network for tasks such as classification, predilection and identification. For a faithful representation of the spectrum, it is sufficient to observe the moments at the informative rate rather than the usually higher Nyquist rate. This convenience removes a big deal of burden from the shoulders of the processor following the gamma filter. Very much like the Laplace transform, Poisson moments have the virtue of transforming linear differential equations into algebraic ones. Based on this property, one can linearly solve for the unknown parameters of an autoregressive moving average (ARMA) system simply by observing the Poisson moments of the system input and the output at finite number of time instants. Although the method doesn't put any restrictions on the choice of the filter time scale and the observation times, in practice, these parameters play a significant role in determining the accuracy of the results. If the parameters are not selected properly, the result tend to be ill-conditioned. This study provides some insight into the choice of the time scale.

Subjects/Keywords: Approximation; Bandwidth; Estimation methods; Interpolation; Mathematical vectors; Polynomials; Propagation delay; Signals; Spectral methods; Taylor series; Electric filters – Mathematical models; Signal processing – Mathematical models

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Celebi, Samel, 1. (. D. ). (1995). Representation of locally stationary signals using lowpass moments. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UF00082352

Chicago Manual of Style (16^th Edition):

Celebi, Samel, 1966- ( Dissertant ). “Representation of locally stationary signals using lowpass moments.” 1995. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UF00082352.

MLA Handbook (7^th Edition):

Celebi, Samel, 1966- ( Dissertant ). “Representation of locally stationary signals using lowpass moments.” 1995. Web. 13 Dec 2019.

Vancouver:

Celebi, Samel 1(D). Representation of locally stationary signals using lowpass moments. [Internet] [Doctoral dissertation]. University of Florida; 1995. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UF00082352.

Council of Science Editors:

Celebi, Samel 1(D). Representation of locally stationary signals using lowpass moments. [Doctoral Dissertation]. University of Florida; 1995. Available from: http://ufdc.ufl.edu/UF00082352

University of Florida

26. Fan, Jian, 1954-. Overcomplete wavelet representations with applications in image processing.

Degree: PhD, Computer and Information Science Engineering, 1997, University of Florida

URL: http://ufdc.ufl.edu/AA00034746

Subjects/Keywords: Approximation; Dyadics; Fourier transformations; Frequency response; Image filters; Image processing; Mathematical vectors; Signals; Symmetry; Wavelet analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Fan, Jian, 1. (1997). Overcomplete wavelet representations with applications in image processing. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00034746

Chicago Manual of Style (16^th Edition):

Fan, Jian, 1954-. “Overcomplete wavelet representations with applications in image processing.” 1997. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00034746.

MLA Handbook (7^th Edition):

Fan, Jian, 1954-. “Overcomplete wavelet representations with applications in image processing.” 1997. Web. 13 Dec 2019.

Vancouver:

Fan, Jian 1. Overcomplete wavelet representations with applications in image processing. [Internet] [Doctoral dissertation]. University of Florida; 1997. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00034746.

Council of Science Editors:

Fan, Jian 1. Overcomplete wavelet representations with applications in image processing. [Doctoral Dissertation]. University of Florida; 1997. Available from: http://ufdc.ufl.edu/AA00034746

University of Florida

27. Wunderli, Thomas. Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal.

Degree: PhD, Mathematics, 2003, University of Florida

URL: http://ufdc.ufl.edu/AA00040524

Subjects/Keywords: Approximation; Convexity; Data smoothing; Image processing; Images; Mathematical independent variables; Mathematical theorems; Mathematics; Perceptron convergence procedure; Uniqueness

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wunderli, T. (2003). Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00040524

Chicago Manual of Style (16^th Edition):

Wunderli, Thomas. “Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal.” 2003. Doctoral Dissertation, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/AA00040524.

MLA Handbook (7^th Edition):

Wunderli, Thomas. “Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal.” 2003. Web. 13 Dec 2019.

Vancouver:

Wunderli T. Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal. [Internet] [Doctoral dissertation]. University of Florida; 2003. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/AA00040524.

Council of Science Editors:

Wunderli T. Partial Differential equations-based image processing in the space of bounded variation using selective smoothing functionals for noise removal. [Doctoral Dissertation]. University of Florida; 2003. Available from: http://ufdc.ufl.edu/AA00040524

University of Florida

28. Rahman, Haseeb Ahmad ( Dissertant ). Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy.

Degree: M.S, Biomedical Engineering, 2004, University of Florida

URL: http://ufdc.ufl.edu/UFE0002640

► An understanding of the relationship between knee joint kinematics and injury or disease (e.g., osteoarthritis) can be best achieved by studying the joint under in… (more)

Subjects/Keywords: Artists models; Bones; Femur; Fluoroscopy; Image processing; Image rotation; Kinematics; Knee joint; Knees; Patella

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Rahman, H. A. (. D. ). (2004). Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0002640

Chicago Manual of Style (16^th Edition):

Rahman, Haseeb Ahmad ( Dissertant ). “Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy.” 2004. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0002640.

MLA Handbook (7^th Edition):

Rahman, Haseeb Ahmad ( Dissertant ). “Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy.” 2004. Web. 13 Dec 2019.

Vancouver:

Rahman HA(D). Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy. [Internet] [Masters thesis]. University of Florida; 2004. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0002640.

Council of Science Editors:

Rahman HA(D). Accurate measurement of three-dimensional natural knee kinematics using single-plane fluoroscopy. [Masters Thesis]. University of Florida; 2004. Available from: http://ufdc.ufl.edu/UFE0002640

University of Florida

29. Shi, Hongchi. Parallel image processing with image algebra on SIMD mesh-connected computers.

Degree: University of Florida

URL: http://ufdc.ufl.edu/UF00090910

Subjects/Keywords: Algebra; Algorithms; Computer algebra systems; Computer technology; Data models; Image analysis; Image processing; Parallel computing; Pixels; Single instruction multiple data computers

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Shi, H. (n.d.). Parallel image processing with image algebra on SIMD mesh-connected computers. (Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UF00090910

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shi, Hongchi. “Parallel image processing with image algebra on SIMD mesh-connected computers.” Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UF00090910.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shi, Hongchi. “Parallel image processing with image algebra on SIMD mesh-connected computers.” Web. 13 Dec 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Shi H. Parallel image processing with image algebra on SIMD mesh-connected computers. [Internet] [Thesis]. University of Florida; [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UF00090910.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Shi H. Parallel image processing with image algebra on SIMD mesh-connected computers. [Thesis]. University of Florida; Available from: http://ufdc.ufl.edu/UF00090910

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

University of Florida

30. Kumthekar, Aditee ( Dissertant ). Affine image registration using minimum spanning tree entropies.

Degree: M.S, Computer and Information Science and Engineering, 2004, University of Florida

URL: http://ufdc.ufl.edu/UFE0004885

► The various environmental factors, settings of the image acquisition device and the material properties of a object directly affect the formation of an image. Registration… (more)

Subjects/Keywords: Coordinate transformations; Density estimation; Entropy; Histograms; Image rotation; Images; Images of transformations; Mathematical optima; Pixels; Timber; Image analysis; Image processing – Digital techniques

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kumthekar, A. (. D. ). (2004). Affine image registration using minimum spanning tree entropies. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0004885

Chicago Manual of Style (16^th Edition):

Kumthekar, Aditee ( Dissertant ). “Affine image registration using minimum spanning tree entropies.” 2004. Masters Thesis, University of Florida. Accessed December 13, 2019. http://ufdc.ufl.edu/UFE0004885.

MLA Handbook (7^th Edition):

Kumthekar, Aditee ( Dissertant ). “Affine image registration using minimum spanning tree entropies.” 2004. Web. 13 Dec 2019.

Vancouver:

Kumthekar A(D). Affine image registration using minimum spanning tree entropies. [Internet] [Masters thesis]. University of Florida; 2004. [cited 2019 Dec 13]. Available from: http://ufdc.ufl.edu/UFE0004885.

Council of Science Editors:

Kumthekar A(D). Affine image registration using minimum spanning tree entropies. [Masters Thesis]. University of Florida; 2004. Available from: http://ufdc.ufl.edu/UFE0004885

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