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You searched for subject:(Image processing Mathematics). Showing records 1 – 30 of 204 total matches.

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Ryerson University

1. Marsousi, Mahdi. Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation.

Degree: 2012, Ryerson University

 The Sparse representation research field and applications have been rapidly growing during the past 15 years. The use of overcomplete dictionaries in sparse representation has… (more)

Subjects/Keywords: Signal processing  – Mathematics; Image processing

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

APA (6th Edition):

Marsousi, M. (2012). Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1623

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

Chicago Manual of Style (16th Edition):

Marsousi, Mahdi. “Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation.” 2012. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1623.

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

MLA Handbook (7th Edition):

Marsousi, Mahdi. “Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation.” 2012. Web. 26 Jan 2020.

Vancouver:

Marsousi M. Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation. [Internet] [Thesis]. Ryerson University; 2012. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1623.

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

Council of Science Editors:

Marsousi M. Variable Length K-SVD: A New Dictionary Learning Approach and Multi-Stage OMP Method for Sparse Representation. [Thesis]. Ryerson University; 2012. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1623

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


Ryerson University

2. Rzeszutek, Richard. Image segmentation through the scale-space random walker.

Degree: 2009, Ryerson University

 This thesis proposes an extension to the Random Walks assisted segmentation algorithm that allows it to operate on a scale-space. Scale-space is a multi-resolution signal… (more)

Subjects/Keywords: Image processing  – Mathematics; Random walks (Mathematics); Computer vision; Image processing  – Mathematics

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

APA (6th Edition):

Rzeszutek, R. (2009). Image segmentation through the scale-space random walker. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1295

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

Chicago Manual of Style (16th Edition):

Rzeszutek, Richard. “Image segmentation through the scale-space random walker.” 2009. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1295.

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

MLA Handbook (7th Edition):

Rzeszutek, Richard. “Image segmentation through the scale-space random walker.” 2009. Web. 26 Jan 2020.

Vancouver:

Rzeszutek R. Image segmentation through the scale-space random walker. [Internet] [Thesis]. Ryerson University; 2009. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1295.

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

Council of Science Editors:

Rzeszutek R. Image segmentation through the scale-space random walker. [Thesis]. Ryerson University; 2009. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1295

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


Ryerson University

3. Venkataraman, Anuyogam. Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques.

Degree: 2014, Ryerson University

 With the increasing utilization of X-ray Computed Tomography (CT) in medical diagnosis, obtaining higher quality image with lower exposure to radiation is a highly challenging… (more)

Subjects/Keywords: Tomography; Image reconstruction  – Mathematical models; Algorithms; Image processing  – Digital techniques; Image processing  – Mathematics; Image processing  – Data processing

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APA (6th Edition):

Venkataraman, A. (2014). Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3509

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

Chicago Manual of Style (16th Edition):

Venkataraman, Anuyogam. “Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques.” 2014. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A3509.

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

MLA Handbook (7th Edition):

Venkataraman, Anuyogam. “Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques.” 2014. Web. 26 Jan 2020.

Vancouver:

Venkataraman A. Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques. [Internet] [Thesis]. Ryerson University; 2014. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3509.

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

Council of Science Editors:

Venkataraman A. Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques. [Thesis]. Ryerson University; 2014. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3509

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


Ryerson University

4. Ghadrdan, Samira. Low-dose computed tomography image denoising based on joint wavelet and sparse representation.

Degree: 2014, Ryerson University

 One of the most challenging issues in low dose computed tomography (CT) imaging is image denoising and signal enhancement. Sparse representational methods have shown initial… (more)

Subjects/Keywords: Tomography; Image reconstruction  – Mathematical models; Algorithms; Image processing  – Digital techniques; Image processing  – Mathematics; Image processing  – Data processing; Wavelets

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

APA (6th Edition):

Ghadrdan, S. (2014). Low-dose computed tomography image denoising based on joint wavelet and sparse representation. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3334

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

Chicago Manual of Style (16th Edition):

Ghadrdan, Samira. “Low-dose computed tomography image denoising based on joint wavelet and sparse representation.” 2014. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A3334.

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

MLA Handbook (7th Edition):

Ghadrdan, Samira. “Low-dose computed tomography image denoising based on joint wavelet and sparse representation.” 2014. Web. 26 Jan 2020.

Vancouver:

Ghadrdan S. Low-dose computed tomography image denoising based on joint wavelet and sparse representation. [Internet] [Thesis]. Ryerson University; 2014. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3334.

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

Council of Science Editors:

Ghadrdan S. Low-dose computed tomography image denoising based on joint wavelet and sparse representation. [Thesis]. Ryerson University; 2014. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3334

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


Ryerson University

5. Khodabandeh, Aryan. Computed tomography noise reduction based on total variation minimization and morphological component analysis.

Degree: 2015, Ryerson University

 X-ray Computed Tomography (CT) scans, while useful, emit harmful radiation which is why low-dose image acquisition is desired. However, noise corruption in these cases is… (more)

Subjects/Keywords: Image processing  – Mathematical models; Imaging systems in medicine; Noise control; Image processing  – Mathematics; Image processing  – Digital techniques  – Mathematics

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

APA (6th Edition):

Khodabandeh, A. (2015). Computed tomography noise reduction based on total variation minimization and morphological component analysis. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3725

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

Chicago Manual of Style (16th Edition):

Khodabandeh, Aryan. “Computed tomography noise reduction based on total variation minimization and morphological component analysis.” 2015. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A3725.

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

MLA Handbook (7th Edition):

Khodabandeh, Aryan. “Computed tomography noise reduction based on total variation minimization and morphological component analysis.” 2015. Web. 26 Jan 2020.

Vancouver:

Khodabandeh A. Computed tomography noise reduction based on total variation minimization and morphological component analysis. [Internet] [Thesis]. Ryerson University; 2015. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3725.

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

Council of Science Editors:

Khodabandeh A. Computed tomography noise reduction based on total variation minimization and morphological component analysis. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3725

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


Kansas State University

6. Silwal, Sharad Deep. Bayesian inference and wavelet methods in image processing.

Degree: MS, Department of Statistics, 2009, Kansas State University

 This report addresses some mathematical and statistical techniques of image processing and their computational implementation. Fundamental theories have been presented, applied and illustrated with examples.… (more)

Subjects/Keywords: Bayesian Inference; Wavelets; Image denoising; Image processing; Mathematics (0405); Statistics (0463)

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APA (6th Edition):

Silwal, S. D. (2009). Bayesian inference and wavelet methods in image processing. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/2355

Chicago Manual of Style (16th Edition):

Silwal, Sharad Deep. “Bayesian inference and wavelet methods in image processing.” 2009. Masters Thesis, Kansas State University. Accessed January 26, 2020. http://hdl.handle.net/2097/2355.

MLA Handbook (7th Edition):

Silwal, Sharad Deep. “Bayesian inference and wavelet methods in image processing.” 2009. Web. 26 Jan 2020.

Vancouver:

Silwal SD. Bayesian inference and wavelet methods in image processing. [Internet] [Masters thesis]. Kansas State University; 2009. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/2097/2355.

Council of Science Editors:

Silwal SD. Bayesian inference and wavelet methods in image processing. [Masters Thesis]. Kansas State University; 2009. Available from: http://hdl.handle.net/2097/2355


Ryerson University

7. Ibrahim, Muhammad T. Novel Filtering Methods for Image and Video Processing Applications.

Degree: 2012, Ryerson University

 During the last few years, digital filtering methods for image/video processing applications have reached a satisfactory level. However, their performance degrades in the presence of… (more)

Subjects/Keywords: Image processing  – Digital technique; Signal processing  – Digital technique; Image transmission; Digital video; Digital filters (Mathematics); Signal processing  – Mathematics

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

APA (6th Edition):

Ibrahim, M. T. (2012). Novel Filtering Methods for Image and Video Processing Applications. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1759

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

Chicago Manual of Style (16th Edition):

Ibrahim, Muhammad T. “Novel Filtering Methods for Image and Video Processing Applications.” 2012. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1759.

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

MLA Handbook (7th Edition):

Ibrahim, Muhammad T. “Novel Filtering Methods for Image and Video Processing Applications.” 2012. Web. 26 Jan 2020.

Vancouver:

Ibrahim MT. Novel Filtering Methods for Image and Video Processing Applications. [Internet] [Thesis]. Ryerson University; 2012. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1759.

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

Council of Science Editors:

Ibrahim MT. Novel Filtering Methods for Image and Video Processing Applications. [Thesis]. Ryerson University; 2012. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1759

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


UCLA

8. Dragomiretskiy, Konstantin. Variational Methods in Signal Decomposition and Image Processing.

Degree: Mathematics, 2015, UCLA

 The work presented in this dissertation is motivated by classical problems in signal and image processing from the perspective of variational and PDE-based methods. Analytically… (more)

Subjects/Keywords: Applied mathematics; Image Processing; Image Segmentation; Mode Decomposition; Signal Decomposition; Signal Processing; Variational Methods

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

APA (6th Edition):

Dragomiretskiy, K. (2015). Variational Methods in Signal Decomposition and Image Processing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/4zx6s9zs

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

Chicago Manual of Style (16th Edition):

Dragomiretskiy, Konstantin. “Variational Methods in Signal Decomposition and Image Processing.” 2015. Thesis, UCLA. Accessed January 26, 2020. http://www.escholarship.org/uc/item/4zx6s9zs.

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

MLA Handbook (7th Edition):

Dragomiretskiy, Konstantin. “Variational Methods in Signal Decomposition and Image Processing.” 2015. Web. 26 Jan 2020.

Vancouver:

Dragomiretskiy K. Variational Methods in Signal Decomposition and Image Processing. [Internet] [Thesis]. UCLA; 2015. [cited 2020 Jan 26]. Available from: http://www.escholarship.org/uc/item/4zx6s9zs.

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

Council of Science Editors:

Dragomiretskiy K. Variational Methods in Signal Decomposition and Image Processing. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/4zx6s9zs

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


Ryerson University

9. Dong, Nan. Content-independent orientation detection with histogram of optimized local binary pattern.

Degree: 2009, Ryerson University

 This thesis is primarily concerned with the introduction of a new approach to the general problem of automatic image orientation detection. Inspired by the local… (more)

Subjects/Keywords: Image processing  – Digital techniques; Image analysis  – Data processing; Algorithms; Binary system (Mathematics)

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

APA (6th Edition):

Dong, N. (2009). Content-independent orientation detection with histogram of optimized local binary pattern. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1025

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

Chicago Manual of Style (16th Edition):

Dong, Nan. “Content-independent orientation detection with histogram of optimized local binary pattern.” 2009. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1025.

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

MLA Handbook (7th Edition):

Dong, Nan. “Content-independent orientation detection with histogram of optimized local binary pattern.” 2009. Web. 26 Jan 2020.

Vancouver:

Dong N. Content-independent orientation detection with histogram of optimized local binary pattern. [Internet] [Thesis]. Ryerson University; 2009. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1025.

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

Council of Science Editors:

Dong N. Content-independent orientation detection with histogram of optimized local binary pattern. [Thesis]. Ryerson University; 2009. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1025

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


Lehigh University

10. Kim, Edward. Toward Large Scale Semantic Image Understanding and Retrieval.

Degree: PhD, Computer Science, 2013, Lehigh University

 Semantic image retrieval is a multifaceted, highly complex problem. Not only does the solution to this problem require advanced image processing and computer vision techniques,… (more)

Subjects/Keywords: Computer Vision; Image Processing; Image Retrieval; Semantic Web; Computer Sciences; Physical Sciences and Mathematics

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

APA (6th Edition):

Kim, E. (2013). Toward Large Scale Semantic Image Understanding and Retrieval. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/1712

Chicago Manual of Style (16th Edition):

Kim, Edward. “Toward Large Scale Semantic Image Understanding and Retrieval.” 2013. Doctoral Dissertation, Lehigh University. Accessed January 26, 2020. https://preserve.lehigh.edu/etd/1712.

MLA Handbook (7th Edition):

Kim, Edward. “Toward Large Scale Semantic Image Understanding and Retrieval.” 2013. Web. 26 Jan 2020.

Vancouver:

Kim E. Toward Large Scale Semantic Image Understanding and Retrieval. [Internet] [Doctoral dissertation]. Lehigh University; 2013. [cited 2020 Jan 26]. Available from: https://preserve.lehigh.edu/etd/1712.

Council of Science Editors:

Kim E. Toward Large Scale Semantic Image Understanding and Retrieval. [Doctoral Dissertation]. Lehigh University; 2013. Available from: https://preserve.lehigh.edu/etd/1712


Ryerson University

11. Sharifymoghaddam, Mina. Image Denoising in Spatial and Transform Domains.

Degree: 2015, Ryerson University

Image denoising is an inseparable pre-processing step of many image processing algorithms. Two mostly used image denoising algorithms are Nonlocal Means (NLM) and Block Matching… (more)

Subjects/Keywords: Imaging systems  – Image quality; Digital filters (Mathematics); Electronic noise  – Prevention; Image processing  – Digital techniques

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

APA (6th Edition):

Sharifymoghaddam, M. (2015). Image Denoising in Spatial and Transform Domains. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A4274

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

Chicago Manual of Style (16th Edition):

Sharifymoghaddam, Mina. “Image Denoising in Spatial and Transform Domains.” 2015. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A4274.

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

MLA Handbook (7th Edition):

Sharifymoghaddam, Mina. “Image Denoising in Spatial and Transform Domains.” 2015. Web. 26 Jan 2020.

Vancouver:

Sharifymoghaddam M. Image Denoising in Spatial and Transform Domains. [Internet] [Thesis]. Ryerson University; 2015. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4274.

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

Council of Science Editors:

Sharifymoghaddam M. Image Denoising in Spatial and Transform Domains. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4274

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


Virginia Commonwealth University

12. Wenan, Chen. Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making.

Degree: PhD, Computer Science, 2010, Virginia Commonwealth University

 The severity of traumatic brain injury (TBI) is known to be characterized by the shift of the middle line in brain as the ventricular system… (more)

Subjects/Keywords: CT Image; Midline Shift; Decision Making; Medical image processing; Computer Sciences; Physical Sciences and Mathematics

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

APA (6th Edition):

Wenan, C. (2010). Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/121

Chicago Manual of Style (16th Edition):

Wenan, Chen. “Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making.” 2010. Doctoral Dissertation, Virginia Commonwealth University. Accessed January 26, 2020. https://scholarscompass.vcu.edu/etd/121.

MLA Handbook (7th Edition):

Wenan, Chen. “Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making.” 2010. Web. 26 Jan 2020.

Vancouver:

Wenan C. Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2010. [cited 2020 Jan 26]. Available from: https://scholarscompass.vcu.edu/etd/121.

Council of Science Editors:

Wenan C. Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making. [Doctoral Dissertation]. Virginia Commonwealth University; 2010. Available from: https://scholarscompass.vcu.edu/etd/121


East Carolina University

13. Kirk, Samantha. Mathematical Aspects of Image Processing.

Degree: 2014, East Carolina University

 In this thesis, image processing is explored from a mathematical point of view. After defining a digitized image, techniques for adjusting resolution are discussed. Image(more)

Subjects/Keywords: Mathematics; Transform; Image processing – Mathematical models; Fourier transformations

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APA (6th Edition):

Kirk, S. (2014). Mathematical Aspects of Image Processing. (Thesis). East Carolina University. Retrieved from http://hdl.handle.net/10342/4406

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

Chicago Manual of Style (16th Edition):

Kirk, Samantha. “Mathematical Aspects of Image Processing.” 2014. Thesis, East Carolina University. Accessed January 26, 2020. http://hdl.handle.net/10342/4406.

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

MLA Handbook (7th Edition):

Kirk, Samantha. “Mathematical Aspects of Image Processing.” 2014. Web. 26 Jan 2020.

Vancouver:

Kirk S. Mathematical Aspects of Image Processing. [Internet] [Thesis]. East Carolina University; 2014. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/10342/4406.

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

Council of Science Editors:

Kirk S. Mathematical Aspects of Image Processing. [Thesis]. East Carolina University; 2014. Available from: http://hdl.handle.net/10342/4406

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


UCLA

14. Zhu, Wei. Nonlocal Variational Methods in Image and Data Processing.

Degree: Mathematics, 2017, UCLA

 In this dissertation, two nonlocal variational models for image and data processing are presented: nonlocal total variation (NLTV) for unsupervised hyperspectral image classification, and low… (more)

Subjects/Keywords: Applied mathematics; hyperspectral images; image processing; manifold learning; nonlocal variational methods

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APA (6th Edition):

Zhu, W. (2017). Nonlocal Variational Methods in Image and Data Processing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1b16b6q7

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

Chicago Manual of Style (16th Edition):

Zhu, Wei. “Nonlocal Variational Methods in Image and Data Processing.” 2017. Thesis, UCLA. Accessed January 26, 2020. http://www.escholarship.org/uc/item/1b16b6q7.

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

MLA Handbook (7th Edition):

Zhu, Wei. “Nonlocal Variational Methods in Image and Data Processing.” 2017. Web. 26 Jan 2020.

Vancouver:

Zhu W. Nonlocal Variational Methods in Image and Data Processing. [Internet] [Thesis]. UCLA; 2017. [cited 2020 Jan 26]. Available from: http://www.escholarship.org/uc/item/1b16b6q7.

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

Council of Science Editors:

Zhu W. Nonlocal Variational Methods in Image and Data Processing. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/1b16b6q7

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

15. Muller, Simon Adriaan. Planar segmentation of range images.

Degree: MSc, Mathematical Sciences, 2013, Stellenbosch University

ENGLISH ABSTRACT: Range images are images that store at each pixel the distance between the sensor and a particular point in the observed scene, instead… (more)

Subjects/Keywords: Applied mathematics; Image processing

…limited to investigating options in the field of range image segmentation, with a focus on… …points in the image. While obtaining relative distances between points or objects is possible… …image can be obtained from the captured data, along with a scaling algorithm that allows… …absolute distances to be calculated and a point cloud to be generated from the range image. An… …reflection properties of surfaces, structure, viewing angle, etc. A range image maintains only the… 

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

APA (6th Edition):

Muller, S. A. (2013). Planar segmentation of range images. (Masters Thesis). Stellenbosch University. Retrieved from http://hdl.handle.net/10019.1/80168

Chicago Manual of Style (16th Edition):

Muller, Simon Adriaan. “Planar segmentation of range images.” 2013. Masters Thesis, Stellenbosch University. Accessed January 26, 2020. http://hdl.handle.net/10019.1/80168.

MLA Handbook (7th Edition):

Muller, Simon Adriaan. “Planar segmentation of range images.” 2013. Web. 26 Jan 2020.

Vancouver:

Muller SA. Planar segmentation of range images. [Internet] [Masters thesis]. Stellenbosch University; 2013. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/10019.1/80168.

Council of Science Editors:

Muller SA. Planar segmentation of range images. [Masters Thesis]. Stellenbosch University; 2013. Available from: http://hdl.handle.net/10019.1/80168


Virginia Commonwealth University

16. Olsen, Grace. Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System.

Degree: PhD, Computer Science, 2010, Virginia Commonwealth University

 Computer-aided education in dental schools is greatly needed in order to reduce the need for human instructors to provide guidance and feedback as students practice… (more)

Subjects/Keywords: Image Processing; Machine Learning; Computer Sciences; Physical Sciences and Mathematics

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

APA (6th Edition):

Olsen, G. (2010). Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/2052

Chicago Manual of Style (16th Edition):

Olsen, Grace. “Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System.” 2010. Doctoral Dissertation, Virginia Commonwealth University. Accessed January 26, 2020. https://scholarscompass.vcu.edu/etd/2052.

MLA Handbook (7th Edition):

Olsen, Grace. “Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System.” 2010. Web. 26 Jan 2020.

Vancouver:

Olsen G. Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2010. [cited 2020 Jan 26]. Available from: https://scholarscompass.vcu.edu/etd/2052.

Council of Science Editors:

Olsen G. Fundamental Work Toward an Image Processing-Empowered Dental Intelligent Educational System. [Doctoral Dissertation]. Virginia Commonwealth University; 2010. Available from: https://scholarscompass.vcu.edu/etd/2052


Hong Kong University of Science and Technology

17. Dai, Jingjing. Digital image and video denoising in multimedia applications.

Degree: 2012, Hong Kong University of Science and Technology

 Noise reduction (denoising) is of crucial importance in multimedia applications, as digital images and videos are often contaminated by noise during acquisition, storage, and transmission,… (more)

Subjects/Keywords: Image processing  – Digital techniques ; Digital video ; Digital filters (Mathematics)

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

APA (6th Edition):

Dai, J. (2012). Digital image and video denoising in multimedia applications. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-7796 ; https://doi.org/10.14711/thesis-b1198656 ; http://repository.ust.hk/ir/bitstream/1783.1-7796/1/th_redirect.html

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

Chicago Manual of Style (16th Edition):

Dai, Jingjing. “Digital image and video denoising in multimedia applications.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed January 26, 2020. http://repository.ust.hk/ir/Record/1783.1-7796 ; https://doi.org/10.14711/thesis-b1198656 ; http://repository.ust.hk/ir/bitstream/1783.1-7796/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Dai, Jingjing. “Digital image and video denoising in multimedia applications.” 2012. Web. 26 Jan 2020.

Vancouver:

Dai J. Digital image and video denoising in multimedia applications. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2020 Jan 26]. Available from: http://repository.ust.hk/ir/Record/1783.1-7796 ; https://doi.org/10.14711/thesis-b1198656 ; http://repository.ust.hk/ir/bitstream/1783.1-7796/1/th_redirect.html.

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

Council of Science Editors:

Dai J. Digital image and video denoising in multimedia applications. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: http://repository.ust.hk/ir/Record/1783.1-7796 ; https://doi.org/10.14711/thesis-b1198656 ; http://repository.ust.hk/ir/bitstream/1783.1-7796/1/th_redirect.html

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


Ryerson University

18. Taherian, Negar. K-means clustering based tone-mapping operator for high dynamic range video.

Degree: 2017, Ryerson University

 The field of high dynamic range (HDR) imaging deals with capturing the luminance of a natural scene, usually varying between 10−3 to 105 cd/m2 and… (more)

Subjects/Keywords: Computer algorithms.; High dynamic range imaging  – Mathematics.; Image processing  – Digital techniques.; Cluster analysis  – Data processing.

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

APA (6th Edition):

Taherian, N. (2017). K-means clustering based tone-mapping operator for high dynamic range video. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A6927

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

Chicago Manual of Style (16th Edition):

Taherian, Negar. “K-means clustering based tone-mapping operator for high dynamic range video.” 2017. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A6927.

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

MLA Handbook (7th Edition):

Taherian, Negar. “K-means clustering based tone-mapping operator for high dynamic range video.” 2017. Web. 26 Jan 2020.

Vancouver:

Taherian N. K-means clustering based tone-mapping operator for high dynamic range video. [Internet] [Thesis]. Ryerson University; 2017. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6927.

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

Council of Science Editors:

Taherian N. K-means clustering based tone-mapping operator for high dynamic range video. [Thesis]. Ryerson University; 2017. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6927

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


University of California – San Diego

19. Preskitt, Brian Patrick. Phase Retrieval from Locally Supported Measurements.

Degree: Mathematics, 2018, University of California – San Diego

 In this dissertation, we study a new approach to the problem of phase retrieval, which is the task of reconstructing a complex-valued signal from magnitude-only… (more)

Subjects/Keywords: Applied mathematics; Mathematics; Physics; Angular Synchronization; Image processing; Optics; Phase Retrieval; Ptychography; X-ray crystallography

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APA (6th Edition):

Preskitt, B. P. (2018). Phase Retrieval from Locally Supported Measurements. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/97v5k8j9

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

Chicago Manual of Style (16th Edition):

Preskitt, Brian Patrick. “Phase Retrieval from Locally Supported Measurements.” 2018. Thesis, University of California – San Diego. Accessed January 26, 2020. http://www.escholarship.org/uc/item/97v5k8j9.

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

MLA Handbook (7th Edition):

Preskitt, Brian Patrick. “Phase Retrieval from Locally Supported Measurements.” 2018. Web. 26 Jan 2020.

Vancouver:

Preskitt BP. Phase Retrieval from Locally Supported Measurements. [Internet] [Thesis]. University of California – San Diego; 2018. [cited 2020 Jan 26]. Available from: http://www.escholarship.org/uc/item/97v5k8j9.

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

Council of Science Editors:

Preskitt BP. Phase Retrieval from Locally Supported Measurements. [Thesis]. University of California – San Diego; 2018. Available from: http://www.escholarship.org/uc/item/97v5k8j9

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


Stellenbosch University

20. Profitt, Barton. Background subtraction algorithms for a video based system.

Degree: MScEng (Mathematical Sciences, Mathematical Sciences, 2009, Stellenbosch University

ENGLISH ABSTRACT: To reliably classify parts of an image sequence as foreground or background is an important part of many computer vision systems, such as… (more)

Subjects/Keywords: Applied mathematics; Dissertations  – Applied mathematics; Algorithms; Computer vision; Image processing; Mathematical Sciences

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

APA (6th Edition):

Profitt, B. (2009). Background subtraction algorithms for a video based system. (Masters Thesis). Stellenbosch University. Retrieved from http://hdl.handle.net/10019.1/2303

Chicago Manual of Style (16th Edition):

Profitt, Barton. “Background subtraction algorithms for a video based system.” 2009. Masters Thesis, Stellenbosch University. Accessed January 26, 2020. http://hdl.handle.net/10019.1/2303.

MLA Handbook (7th Edition):

Profitt, Barton. “Background subtraction algorithms for a video based system.” 2009. Web. 26 Jan 2020.

Vancouver:

Profitt B. Background subtraction algorithms for a video based system. [Internet] [Masters thesis]. Stellenbosch University; 2009. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/10019.1/2303.

Council of Science Editors:

Profitt B. Background subtraction algorithms for a video based system. [Masters Thesis]. Stellenbosch University; 2009. Available from: http://hdl.handle.net/10019.1/2303


Ryerson University

21. Patel, Sidhdharthkumar. Adaptive Exposure Fusion for HDR Imaging.

Degree: 2015, Ryerson University

 HDR images are usually generated by fusing sequence of images captured with variable exposure time. Exposure Fusion is a technique that directly fuses the exposure… (more)

Subjects/Keywords: Computer vision; Image processing; Imaging systems; Image processing  – Mathematics; Motion  – Mathematical models; Imaging systems  – Digital techniques

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

APA (6th Edition):

Patel, S. (2015). Adaptive Exposure Fusion for HDR Imaging. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A4381

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

Chicago Manual of Style (16th Edition):

Patel, Sidhdharthkumar. “Adaptive Exposure Fusion for HDR Imaging.” 2015. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A4381.

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

MLA Handbook (7th Edition):

Patel, Sidhdharthkumar. “Adaptive Exposure Fusion for HDR Imaging.” 2015. Web. 26 Jan 2020.

Vancouver:

Patel S. Adaptive Exposure Fusion for HDR Imaging. [Internet] [Thesis]. Ryerson University; 2015. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4381.

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

Council of Science Editors:

Patel S. Adaptive Exposure Fusion for HDR Imaging. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A4381

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


University of Florida

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

Degree: PhD, Mathematics, 2012, University of Florida

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

APA (6th 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 (16th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Doctoral Dissertation, University of Florida. Accessed January 26, 2020. http://ufdc.ufl.edu/UFE0044953.

MLA Handbook (7th Edition):

Posirca, Iulia M. “Variational Models for Simultaneous Image Segmentation and Noise Removal.” 2012. Web. 26 Jan 2020.

Vancouver:

Posirca IM. Variational Models for Simultaneous Image Segmentation and Noise Removal. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2020 Jan 26]. 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


Hong Kong University of Science and Technology

23. Zeng, Gang. Surface reconstruction from images.

Degree: 2006, Hong Kong University of Science and Technology

 Surface reconstruction from images is an old, fundamental yet difficult problem in computer vision, which has been extensively investigated over the past three decades. Recent… (more)

Subjects/Keywords: Image processing  – Digital techniques ; Image reconstruction ; Image reconstruction  – Mathematics

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

APA (6th Edition):

Zeng, G. (2006). Surface reconstruction from images. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-2804 ; https://doi.org/10.14711/thesis-b931350 ; http://repository.ust.hk/ir/bitstream/1783.1-2804/1/th_redirect.html

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

Chicago Manual of Style (16th Edition):

Zeng, Gang. “Surface reconstruction from images.” 2006. Thesis, Hong Kong University of Science and Technology. Accessed January 26, 2020. http://repository.ust.hk/ir/Record/1783.1-2804 ; https://doi.org/10.14711/thesis-b931350 ; http://repository.ust.hk/ir/bitstream/1783.1-2804/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Zeng, Gang. “Surface reconstruction from images.” 2006. Web. 26 Jan 2020.

Vancouver:

Zeng G. Surface reconstruction from images. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2006. [cited 2020 Jan 26]. Available from: http://repository.ust.hk/ir/Record/1783.1-2804 ; https://doi.org/10.14711/thesis-b931350 ; http://repository.ust.hk/ir/bitstream/1783.1-2804/1/th_redirect.html.

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

Council of Science Editors:

Zeng G. Surface reconstruction from images. [Thesis]. Hong Kong University of Science and Technology; 2006. Available from: http://repository.ust.hk/ir/Record/1783.1-2804 ; https://doi.org/10.14711/thesis-b931350 ; http://repository.ust.hk/ir/bitstream/1783.1-2804/1/th_redirect.html

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


University of Lethbridge

24. Parshakov, Ilia. Automatic class labeling of classified imagery using a hyperspectral library .

Degree: 2012, University of Lethbridge

Image classification is a fundamental information extraction procedure in remote sensing that is used in land-cover and land-use mapping. Despite being considered as a replacement… (more)

Subjects/Keywords: Remote-sensing images  – Data processing; Image processing  – Digital techniques; Pattern recognition systems; Algorithms; Image analysis  – Mathematics; Image analysis  – Data processing; Dissertations, Academic

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

APA (6th Edition):

Parshakov, I. (2012). Automatic class labeling of classified imagery using a hyperspectral library . (Thesis). University of Lethbridge. Retrieved from http://hdl.handle.net/10133/3372

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

Chicago Manual of Style (16th Edition):

Parshakov, Ilia. “Automatic class labeling of classified imagery using a hyperspectral library .” 2012. Thesis, University of Lethbridge. Accessed January 26, 2020. http://hdl.handle.net/10133/3372.

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

MLA Handbook (7th Edition):

Parshakov, Ilia. “Automatic class labeling of classified imagery using a hyperspectral library .” 2012. Web. 26 Jan 2020.

Vancouver:

Parshakov I. Automatic class labeling of classified imagery using a hyperspectral library . [Internet] [Thesis]. University of Lethbridge; 2012. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/10133/3372.

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

Council of Science Editors:

Parshakov I. Automatic class labeling of classified imagery using a hyperspectral library . [Thesis]. University of Lethbridge; 2012. Available from: http://hdl.handle.net/10133/3372

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


Ryerson University

25. Zamyadi, Rouzbeh. A novel framework for compressed sensing brain MRI edge detection and de-noising.

Degree: 2011, Ryerson University

 In this thesis a novel edge detection technique is developed that employs compressed sensing image reconstruction techniques. The ability of compressed sensing noise reduction is… (more)

Subjects/Keywords: Magnetic resonance imaging; Brain  – Mathematical models; Image processing  – Mathematics; Image compression  – Data processing; Wavelets (Mathematics) Algorithms; Noise control; Imaging systems in medicine  – Data processing

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APA (6th Edition):

Zamyadi, R. (2011). A novel framework for compressed sensing brain MRI edge detection and de-noising. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A961

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

Chicago Manual of Style (16th Edition):

Zamyadi, Rouzbeh. “A novel framework for compressed sensing brain MRI edge detection and de-noising.” 2011. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A961.

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

MLA Handbook (7th Edition):

Zamyadi, Rouzbeh. “A novel framework for compressed sensing brain MRI edge detection and de-noising.” 2011. Web. 26 Jan 2020.

Vancouver:

Zamyadi R. A novel framework for compressed sensing brain MRI edge detection and de-noising. [Internet] [Thesis]. Ryerson University; 2011. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A961.

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

Council of Science Editors:

Zamyadi R. A novel framework for compressed sensing brain MRI edge detection and de-noising. [Thesis]. Ryerson University; 2011. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A961

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


Michigan State University

26. Abdolhosseini Moghadam, Abdolreza. Combinatorial methods for compressed sensing.

Degree: 2014, Michigan State University

Thesis Ph. D. Michigan State University. Electrical Engineering 2014.

The inefficiency of the classical signal acquisition systems where a signal is sampled at the Nyquist… (more)

Subjects/Keywords: Compressed sensing (Telecommunication); Image processing – Digital techniques – Mathematics; Signal processing – Digital techniques – Mathematics; Decoders (Electronics); Electrical engineering; Statistics

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APA (6th Edition):

Abdolhosseini Moghadam, A. (2014). Combinatorial methods for compressed sensing. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3021

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

Chicago Manual of Style (16th Edition):

Abdolhosseini Moghadam, Abdolreza. “Combinatorial methods for compressed sensing.” 2014. Thesis, Michigan State University. Accessed January 26, 2020. http://etd.lib.msu.edu/islandora/object/etd:3021.

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

MLA Handbook (7th Edition):

Abdolhosseini Moghadam, Abdolreza. “Combinatorial methods for compressed sensing.” 2014. Web. 26 Jan 2020.

Vancouver:

Abdolhosseini Moghadam A. Combinatorial methods for compressed sensing. [Internet] [Thesis]. Michigan State University; 2014. [cited 2020 Jan 26]. Available from: http://etd.lib.msu.edu/islandora/object/etd:3021.

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

Council of Science Editors:

Abdolhosseini Moghadam A. Combinatorial methods for compressed sensing. [Thesis]. Michigan State University; 2014. Available from: http://etd.lib.msu.edu/islandora/object/etd:3021

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


Ryerson University

27. Julazadeh, Mohammadali. Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms.

Degree: 2012, Ryerson University

 In this thesis a novel classification approach based on sparse representation framework is proposed. The method finds the minimum Euclidian distance between an input patch… (more)

Subjects/Keywords: Diagnostic imaging  – Data processing; Algorithms; Imaging systems in medicine; Image processing  – Digital techniques; Signal processing  – Digital techniques  – Mathematics; Computer vision

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APA (6th Edition):

Julazadeh, M. (2012). Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1870

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

Chicago Manual of Style (16th Edition):

Julazadeh, Mohammadali. “Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms.” 2012. Thesis, Ryerson University. Accessed January 26, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1870.

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

MLA Handbook (7th Edition):

Julazadeh, Mohammadali. “Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms.” 2012. Web. 26 Jan 2020.

Vancouver:

Julazadeh M. Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms. [Internet] [Thesis]. Ryerson University; 2012. [cited 2020 Jan 26]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1870.

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

Council of Science Editors:

Julazadeh M. Medical Image Segmentation and Classification Based on Sparse Representation and Dictionary Learnng Algorithms. [Thesis]. Ryerson University; 2012. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1870

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

28. Nilsson, Niklas. Feature detection for geospatial referencing.

Degree: Physics, 2019, Umeå University

With the drone industry's recent explosive advancement, aerial photography is becoming increasingly important for an array of applications ranging from construction to agriculture. A… (more)

Subjects/Keywords: Feature detection; feature description; feature; image processing; digital image processing; image analysis; aerial photography; drone; Bildanalys; flygfotografi; flygfoto; bildprocessering; Computational Mathematics; Beräkningsmatematik

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APA (6th Edition):

Nilsson, N. (2019). Feature detection for geospatial referencing. (Thesis). Umeå University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-159809

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

Chicago Manual of Style (16th Edition):

Nilsson, Niklas. “Feature detection for geospatial referencing.” 2019. Thesis, Umeå University. Accessed January 26, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-159809.

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

MLA Handbook (7th Edition):

Nilsson, Niklas. “Feature detection for geospatial referencing.” 2019. Web. 26 Jan 2020.

Vancouver:

Nilsson N. Feature detection for geospatial referencing. [Internet] [Thesis]. Umeå University; 2019. [cited 2020 Jan 26]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-159809.

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

Council of Science Editors:

Nilsson N. Feature detection for geospatial referencing. [Thesis]. Umeå University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-159809

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


University of New Mexico

29. Jeromin, Oliver. Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models.

Degree: Electrical and Computer Engineering, 2009, University of New Mexico

 This dissertation focuses on the development of high-quality image reconstruction methods from a limited number of Fourier samples using optimized, stochastic and deterministic sampling geometries.… (more)

Subjects/Keywords: Image reconstruction – Digital techniques.; Image processing – Digital techniques.; Digital filters (Mathematics); Magnetic resonance imaging – Data processing.; Remote sensing – Data processing.; Mathematical optimization.; Kriging.

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

APA (6th Edition):

Jeromin, O. (2009). Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/9807

Chicago Manual of Style (16th Edition):

Jeromin, Oliver. “Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models.” 2009. Doctoral Dissertation, University of New Mexico. Accessed January 26, 2020. http://hdl.handle.net/1928/9807.

MLA Handbook (7th Edition):

Jeromin, Oliver. “Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models.” 2009. Web. 26 Jan 2020.

Vancouver:

Jeromin O. Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models. [Internet] [Doctoral dissertation]. University of New Mexico; 2009. [cited 2020 Jan 26]. Available from: http://hdl.handle.net/1928/9807.

Council of Science Editors:

Jeromin O. Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models. [Doctoral Dissertation]. University of New Mexico; 2009. Available from: http://hdl.handle.net/1928/9807


University of Colorado

30. Charles, Richard Martin. Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images.

Degree: PhD, Applied Mathematics, 2015, University of Colorado

  Recent improvements in computing and technology demand the processing and analysis of huge datasets in a variety of fields. Often the analysis requires the… (more)

Subjects/Keywords: Compression; Image Patches; Nonnegative Matrix Factorization; Pixel Reordering; SVD; Applied Mathematics; Signal Processing

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

APA (6th Edition):

Charles, R. M. (2015). Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/68

Chicago Manual of Style (16th Edition):

Charles, Richard Martin. “Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images.” 2015. Doctoral Dissertation, University of Colorado. Accessed January 26, 2020. https://scholar.colorado.edu/appm_gradetds/68.

MLA Handbook (7th Edition):

Charles, Richard Martin. “Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images.” 2015. Web. 26 Jan 2020.

Vancouver:

Charles RM. Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images. [Internet] [Doctoral dissertation]. University of Colorado; 2015. [cited 2020 Jan 26]. Available from: https://scholar.colorado.edu/appm_gradetds/68.

Council of Science Editors:

Charles RM. Matrix Patch Reordering as a Strategy for Compression, Factorization, and Pattern Detection using Nonnegative Matrix Factorization Applied to Single Images. [Doctoral Dissertation]. University of Colorado; 2015. Available from: https://scholar.colorado.edu/appm_gradetds/68

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