Incoherent dictionary learning and sparse representation for single-image rain removal

The incoherent dictionary learning and sparse representation algorithm was present and it was applied to single-image rain removal.The incoherence of the dictionary was introduced to design a new objective function in the dictionary learning,which addressed the problem of reducing the similarity bet...

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Main Authors: Hong-zhong TANG, Xiang WANG, Xiao-gang ZHANG, Xiao LI, Li-zhen MAO
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2017-07-01
Series:Tongxin xuebao
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Online Access:http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2017149
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author Hong-zhong TANG
Xiang WANG
Xiao-gang ZHANG
Xiao LI
Li-zhen MAO
author_facet Hong-zhong TANG
Xiang WANG
Xiao-gang ZHANG
Xiao LI
Li-zhen MAO
author_sort Hong-zhong TANG
collection DOAJ
description The incoherent dictionary learning and sparse representation algorithm was present and it was applied to single-image rain removal.The incoherence of the dictionary was introduced to design a new objective function in the dictionary learning,which addressed the problem of reducing the similarity between rain atoms and non-rain atoms.The divisibility of rain dictionary and non-rain dictionary could be ensured.Furthermore,the learned dictionary had similar properties to the tight frame and approximates the equiangular tight frame.The high frequency in the rain image could be decomposed into a rain component and a non-rain component by performing sparse coding based learned incoherent dictionary,then the non-rain component in the high frequency and the low frequency were fused to remove rain.Experimental results demonstrate that the learned incoherent dictionary has better performance of sparse representation.The recovered rain-free image has less residual rain,and preserves effectively the edges and details.So the visual effect of recovered image is more sharpness and natural.
format Article
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institution OA Journals
issn 1000-436X
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publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-42fcefed09bc46db82b94560581b48f22025-08-20T02:09:31ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-07-0138283559710706Incoherent dictionary learning and sparse representation for single-image rain removalHong-zhong TANGXiang WANGXiao-gang ZHANGXiao LILi-zhen MAOThe incoherent dictionary learning and sparse representation algorithm was present and it was applied to single-image rain removal.The incoherence of the dictionary was introduced to design a new objective function in the dictionary learning,which addressed the problem of reducing the similarity between rain atoms and non-rain atoms.The divisibility of rain dictionary and non-rain dictionary could be ensured.Furthermore,the learned dictionary had similar properties to the tight frame and approximates the equiangular tight frame.The high frequency in the rain image could be decomposed into a rain component and a non-rain component by performing sparse coding based learned incoherent dictionary,then the non-rain component in the high frequency and the low frequency were fused to remove rain.Experimental results demonstrate that the learned incoherent dictionary has better performance of sparse representation.The recovered rain-free image has less residual rain,and preserves effectively the edges and details.So the visual effect of recovered image is more sharpness and natural.http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2017149incoherent dictionary;dictionary learning;sparse representation;single-image rain removal
spellingShingle Hong-zhong TANG
Xiang WANG
Xiao-gang ZHANG
Xiao LI
Li-zhen MAO
Incoherent dictionary learning and sparse representation for single-image rain removal
Tongxin xuebao
incoherent dictionary;dictionary learning;sparse representation;single-image rain removal
title Incoherent dictionary learning and sparse representation for single-image rain removal
title_full Incoherent dictionary learning and sparse representation for single-image rain removal
title_fullStr Incoherent dictionary learning and sparse representation for single-image rain removal
title_full_unstemmed Incoherent dictionary learning and sparse representation for single-image rain removal
title_short Incoherent dictionary learning and sparse representation for single-image rain removal
title_sort incoherent dictionary learning and sparse representation for single image rain removal
topic incoherent dictionary;dictionary learning;sparse representation;single-image rain removal
url http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2017149
work_keys_str_mv AT hongzhongtang incoherentdictionarylearningandsparserepresentationforsingleimagerainremoval
AT xiangwang incoherentdictionarylearningandsparserepresentationforsingleimagerainremoval
AT xiaogangzhang incoherentdictionarylearningandsparserepresentationforsingleimagerainremoval
AT xiaoli incoherentdictionarylearningandsparserepresentationforsingleimagerainremoval
AT lizhenmao incoherentdictionarylearningandsparserepresentationforsingleimagerainremoval