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: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/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 |
| id | doaj-art-327834dfa6524655bbee41da25f129b2 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-327834dfa6524655bbee41da25f129b22025-01-14T07:12:31ZzhoEditorial 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/zh/article/doi/10.11959/j.issn.1000-436x.2017149/incoherent dictionarydictionary learningsparse representationsingle-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/zh/article/doi/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 |