Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping

<p/> <p>This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identif...

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Main Authors: Wang Chao, Sun Li-Feng, Yang Bo, liu Yi-Ming, Yang Shi-Qiang
Format: Article
Language:English
Published: SpringerOpen 2008-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://asp.eurasipjournals.com/content/2008/165792
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author Wang Chao
Sun Li-Feng
Yang Bo
liu Yi-Ming
Yang Shi-Qiang
author_facet Wang Chao
Sun Li-Feng
Yang Bo
liu Yi-Ming
Yang Shi-Qiang
author_sort Wang Chao
collection DOAJ
description <p/> <p>This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises&#8212;Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results.</p>
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spelling doaj.art-3bfcba20d5944d04ad00036185201ea62022-12-22T02:15:52ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802008-01-0120081165792Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise MappingWang ChaoSun Li-FengYang Boliu Yi-MingYang Shi-Qiang<p/> <p>This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises&#8212;Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results.</p>http://asp.eurasipjournals.com/content/2008/165792
spellingShingle Wang Chao
Sun Li-Feng
Yang Bo
liu Yi-Ming
Yang Shi-Qiang
Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
EURASIP Journal on Advances in Signal Processing
title Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
title_full Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
title_fullStr Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
title_full_unstemmed Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
title_short Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping
title_sort video enhancement using adaptive spatio temporal connective filter and piecewise mapping
url http://asp.eurasipjournals.com/content/2008/165792
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AT yangbo videoenhancementusingadaptivespatiotemporalconnectivefilterandpiecewisemapping
AT liuyiming videoenhancementusingadaptivespatiotemporalconnectivefilterandpiecewisemapping
AT yangshiqiang videoenhancementusingadaptivespatiotemporalconnectivefilterandpiecewisemapping