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Impact of contrast-distorted image on curvelet coefficients

Image quality (IQ) can be degraded due to various types of distortion such as noise, blurring, fast fading (FF), blocking artifacts and contrast distortion. These distortions may occur during operations such as acquisition, compression, storage, transmission, display and post-processing. Contrast di...

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Main Authors: Ahmed, I.T.A., Chen, C.S.D., Hammad, B.T.H.
Format: Conference Paper
Language:English
Published: 2020
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spelling my.uniten.dspace-131482020-03-17T04:55:33Z Impact of contrast-distorted image on curvelet coefficients Ahmed, I.T.A. Chen, C.S.D. Hammad, B.T.H. Image quality (IQ) can be degraded due to various types of distortion such as noise, blurring, fast fading (FF), blocking artifacts and contrast distortion. These distortions may occur during operations such as acquisition, compression, storage, transmission, display and post-processing. Contrast distortion is one of the most common types of distortion. Contrast-distorted image (CDI) is defined as image with low dynamic range of brightness. Most of existing works that used discrete curvelet transform (DCT) are focused on image distortions such as blur, noise, and compression which often affect the high frequency components of an image. Therefore, this paper will study and investigate the application of curvelet transform for CDI. The distributions of curvelet coefficients at different scales have been found to be effective in characterizing good contrast image and contrast-distorted image. The distributions of curvelet coefficients at the coarsest and finest scales can be used to derive potential features in characterizing good contrast images and also contrast-distorted images. © 2018 IEEE. 2020-02-03T03:30:43Z 2020-02-03T03:30:43Z 2019 Conference Paper 10.1109/AiCIS.2018.00018 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description Image quality (IQ) can be degraded due to various types of distortion such as noise, blurring, fast fading (FF), blocking artifacts and contrast distortion. These distortions may occur during operations such as acquisition, compression, storage, transmission, display and post-processing. Contrast distortion is one of the most common types of distortion. Contrast-distorted image (CDI) is defined as image with low dynamic range of brightness. Most of existing works that used discrete curvelet transform (DCT) are focused on image distortions such as blur, noise, and compression which often affect the high frequency components of an image. Therefore, this paper will study and investigate the application of curvelet transform for CDI. The distributions of curvelet coefficients at different scales have been found to be effective in characterizing good contrast image and contrast-distorted image. The distributions of curvelet coefficients at the coarsest and finest scales can be used to derive potential features in characterizing good contrast images and also contrast-distorted images. © 2018 IEEE.
format Conference Paper
author Ahmed, I.T.A.
Chen, C.S.D.
Hammad, B.T.H.
spellingShingle Ahmed, I.T.A.
Chen, C.S.D.
Hammad, B.T.H.
Impact of contrast-distorted image on curvelet coefficients
author_facet Ahmed, I.T.A.
Chen, C.S.D.
Hammad, B.T.H.
author_sort Ahmed, I.T.A.
title Impact of contrast-distorted image on curvelet coefficients
title_short Impact of contrast-distorted image on curvelet coefficients
title_full Impact of contrast-distorted image on curvelet coefficients
title_fullStr Impact of contrast-distorted image on curvelet coefficients
title_full_unstemmed Impact of contrast-distorted image on curvelet coefficients
title_sort impact of contrast-distorted image on curvelet coefficients
publishDate 2020
_version_ 1662758821736480768
score 13.211869

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