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Univerzitet u Beogradu

1. El Mezeni, Dragomir, 1985-. Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja.

Degree: Elektrotehnički fakultet, 2018, Univerzitet u Beogradu

Elektrotehnika i računarstvo - Elektronika / Electrical and Computer Engineering - Electronics

Opseg osvetljaja koji se javlja u prirodnim scenama uveliko prevazilazi mogućnosti standardnih uređaja za snimanje i reprodukciju slike. Ljudski vizuelni sistem je evoluirao, tako da omogući efikasno funkcionisanje i percepciju detalja u uslovima velike promene osvetljaja. Kako bi se omogućila što realnija reprodukcija slika i video sadržaja, potrebno je obezbediti mogućnost snimanja i reprodukcije što šireg dinamičkog opsega osvetljaja. Razvoj tehnika za snimanje je napredovao i danas postoji mogućnost snimanja celokupnog dinamičkog opsega osvetljaja scene korišćenjem standardnih senzora. Razvoj displeja je međutim napredovao sporije i većina displeja koji su danas u upotrebi ima skroman dinamički opseg osvetljaja. Operator za redukciju dinamičkog opsega predstavlja ključnu komponentu sistema za reprodukciju scena širokog dinamičkog opsega (HDR), na standardnim displejima nižeg dinamičkog opsega (LDR)...

Advisors/Committee Members: Saranovac, Lazar. 1961-.

Subjects/Keywords: local tone mapping operator; video hdr tone mapping; temporal coherency; guided filter; fast guided filter

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

APA (6th Edition):

El Mezeni, Dragomir, 1. (2018). Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:18744/bdef:Content/get

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):

El Mezeni, Dragomir, 1985-. “Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja.” 2018. Thesis, Univerzitet u Beogradu. Accessed August 13, 2020. https://fedorabg.bg.ac.rs/fedora/get/o:18744/bdef:Content/get.

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

MLA Handbook (7th Edition):

El Mezeni, Dragomir, 1985-. “Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja.” 2018. Web. 13 Aug 2020.

Vancouver:

El Mezeni, Dragomir 1. Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja. [Internet] [Thesis]. Univerzitet u Beogradu; 2018. [cited 2020 Aug 13]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:18744/bdef:Content/get.

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

Council of Science Editors:

El Mezeni, Dragomir 1. Lokalni operator za reprodukciju slika širokog dinamičkog opsega uz očuvanje detalja. [Thesis]. Univerzitet u Beogradu; 2018. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:18744/bdef:Content/get

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


NSYSU

2. Chang, Cheng-Hao. Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing.

Degree: Master, Computer Science and Engineering, 2017, NSYSU

In an underwater environment, we canât get a clear image because the image is affected by suspended solids. Moreover, the absorption and scattering of light and other issues will occur in the process of underwater transmission. Therefore, the main problems of underwater images are that the scattering phenomenon causes the image to become hazy and the varying degree of attenuation for the light with different wavelength in the water leads to the color distortion. Underwater image is very similar to common hazy image, both of them have the problems of low contrast and color distortion. In the future, if we want to apply the dehazing method to the surveillance system, we must also consider the computational complexity. Recently, a method of Dark Channel Prior has been proposed in [1] to effectively perform single image dehazing, and several studies (e.g., [2-7]) have adopted this method for underwater image enhancement. In this thesis, we improve the underwater image dehazing method based on the Dark Channel Prior. Furthermore, the mean filter is employed to estimate the distance from the object to the camera and the atmospheric light in the water. And then, the transmission map of the hazy image is found, and the edge is corrected by using the simplified fast guided filter to revise the edge. Finally, we can obtain the image without haze. After removing the haze of the underwater image, the next step is correcting the color distortion. In the adopted underwater image restoration method based on Dark Channel Prior, the estimation of the transmission map is an important step. In order to obtain a good visual quality, the guided filter is usually used to correct the edge of the part. In this thesis, a simplified guided filter is proposed and applied to the repair of underwater images to reduce the computational complexity and maintain a good visual quality. In addition, a low-cost architecture of the proposed simplified guided filter is designed to achieve the real-time underwater image correction for the size of Full HD (1920 ï´ 1080). Furthermore, based on the proposed simplified guided filter, we propose a simplified fast guided filter architecture, which significantly improves the speed of guided filtering through image scaling and further reduces the memory usage and area. After these simplifications, it is still able to maintain excellent visual quality. Advisors/Committee Members: Yun-Nan Chang (chair), Pei-Yin Chen (chair), Shiann-Rong Kuang (committee member), Shen-Fu Hsiao (chair), Jer-Min Jou (chair).

Subjects/Keywords: Underwater Image Dehazing; Dark Channel Prior; Fast Guided Filter

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

APA (6th Edition):

Chang, C. (2017). Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721117-161609

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):

Chang, Cheng-Hao. “Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing.” 2017. Thesis, NSYSU. Accessed August 13, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721117-161609.

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

MLA Handbook (7th Edition):

Chang, Cheng-Hao. “Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing.” 2017. Web. 13 Aug 2020.

Vancouver:

Chang C. Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing. [Internet] [Thesis]. NSYSU; 2017. [cited 2020 Aug 13]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721117-161609.

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

Council of Science Editors:

Chang C. Design and Implementation of Fast Guided Filter Hardware Architecture for Underwater Image Dehazing. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721117-161609

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


NSYSU

3. Huang, I-Chang. Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast.

Degree: Master, Computer Science and Engineering, 2018, NSYSU

The impurity in the water affects the clarity of underwater images, leading to great limitations on the application of underwater images in visual analysis and research. In addition to the fact that impurities cause image blurring, different refraction and scattering results are produced depending on the wavelength of the light, when light is transmitted in water,. The color contrast caused by the low contrast of the image and the partial color decay has similar results as the image taken in the fog. In recent years, an effective single image defogging algorithm, Dark Channel Prior, has been proposed in [1]. In many other studies (such as [2-7]), this algorithm is also applied to defogging underwater images. In addition the underexposed photos are often taken, when photographing in the underwater environment. Because the camera is like the human eye, it is not easy to clearly determine the outline, details, etc. of the object, when it receives the smooth, backlit and dark images at the same time. For the case of underexposed images, Pang et al. [8] proposed an enhanced algorithm for images with extremely low contrast. This method is based on the algorithm of Dong[9]. In addition to effectively enhancing the contrast of the image, it can also improve the halo caused by the algorithm of Dong[9]. Therefore, in order to improve these problems in underwater research analysis or underwater monitoring systems, a set of defogging systems that can perform image enhancement for underwater images with extreme contrast differences is indispensable. The defogging system proposed in this thesis contains four major steps: 1) With the RGB color model, the histogram distribution is used to determine whether it is an extreme contrast image or a normal contrast image. Accordingly the subsequent steps have different processing methods. 2) Since the underwater image and the image captured in the fog have similar problems such as contrast reduction and color shift, the dark channel prior can be used to calculate the atmospheric light source of the image. 3) In the dark channel prior, the calculation of the transfer rate is particularly important. Therefore, after estimating the transmission rate map of the image, we use a fast and simple guided filter to correct the edge of the transmission rate map to avoid the phenomenon of halation. 4) Finally, the image is restored by the method of defogging, and different absorption attenuation compensation is performed for the three color channels of RGB. To meet the real-time requirement, this thesis proposes a fast atmospheric light estimator hardware architecture based on the subsampling technique. As the result, the amount of data that needs to be read to estimate atmospheric light is greatly reduced, and the computational speed is much improved. Moreover, based on the algorithm of [8],this thesis also proposes the improved hardware architecture of the defogging system. In order to facilitate the implementation of the hardware architecture, the algorithm is simplified and the high performance… Advisors/Committee Members: Ko-Chi Kuo (chair), Pei-Yin Chen (chair), Shiann-Rong Kuang (committee member), Shen-Fu Hsiao (chair), Xin-Yu Shih (chair).

Subjects/Keywords: Dark Channel Prior; Low Contrast; Fast Guided Filter; Enhancing Image; Underwater Image Dehazing; Extreme Contrast; VLSI Hardware Implementation

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

APA (6th Edition):

Huang, I. (2018). Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0715118-124339

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):

Huang, I-Chang. “Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast.” 2018. Thesis, NSYSU. Accessed August 13, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0715118-124339.

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

MLA Handbook (7th Edition):

Huang, I-Chang. “Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast.” 2018. Web. 13 Aug 2020.

Vancouver:

Huang I. Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast. [Internet] [Thesis]. NSYSU; 2018. [cited 2020 Aug 13]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0715118-124339.

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

Council of Science Editors:

Huang I. Hardware Architecture of Dehazing System for Enhancing Underwater Image with/without Extreme Contrast. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0715118-124339

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

.