Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform
In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform (DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-chan...
Gespeichert in:
| Veröffentlicht in: | Optoelectronics letters 2018-11, Vol.14 (6), p.470-475 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 475 |
|---|---|
| container_issue | 6 |
| container_start_page | 470 |
| container_title | Optoelectronics letters |
| container_volume | 14 |
| creator | Yang, Mao-xiang Tang, Gui-jin Liu, Xiao-hua Wang, Li-qian Cui, Zi-guan Luo, Su-huai |
| description | In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform (DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-channel by dual-tree complex wavelet transform. Next, an improved local adaptive tone mapping method is applied to process the low frequency components of the image, and a soft threshold denoising algorithm is used to denoise the high frequency components of the image. Then, the V-channel is rebuilt and the contrast is adjusted using white balance method. Finally, the processed image is converted back into the RGB color space as the enhanced result. Experimental results show that the proposed method can effectively improve the performance in terms of contrast enhancement, noise reduction and color reproduction. |
| doi_str_mv | 10.1007/s11801-018-8046-5 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2149954087</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2149954087</sourcerecordid><originalsourceid>FETCH-LOGICAL-c316t-68b864fd39eddb3640845456a5f3332fd44553e13b492113f5831556400c9193</originalsourceid><addsrcrecordid>eNp1kE1LAzEQhoMoWLQ_wFvAczSzSXaToxS_oCBIbx5Cdne2H2yzNUmt_femrODJuczAvO87zEPIDfA74Ly6jwCaA-OgmeayZOqMTMAYwRQHcZ7nshIMDFeXZBrjhucSRaWlmZCP-XBg_Xq5SnS9dUuk6FfON7hFn2jtIrZ08PQd09rjN00rHMKROt_Sdu96lgIibYbtrs_Lg_vCHhNNwfnYDWF7TS4610ec_vYrsnh6XMxe2Pzt-XX2MGeNgDKxUte6lF0rDLZtLUrJtVRSlU51Qoiia6VUSiCIWpoCQHRKC1Aq63hjwIgrcjvG7sLwuceY7GbYB58v2gKkMSoHVlkFo6oJQ4wBO7sL-eNwtMDtiaIdKdpM0Z4oWpU9xeiJWeuXGP6S_zf9AGXsc2I</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2149954087</pqid></control><display><type>article</type><title>Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform</title><source>SpringerLink Journals</source><source>Alma/SFX Local Collection</source><creator>Yang, Mao-xiang ; Tang, Gui-jin ; Liu, Xiao-hua ; Wang, Li-qian ; Cui, Zi-guan ; Luo, Su-huai</creator><creatorcontrib>Yang, Mao-xiang ; Tang, Gui-jin ; Liu, Xiao-hua ; Wang, Li-qian ; Cui, Zi-guan ; Luo, Su-huai</creatorcontrib><description>In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform (DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-channel by dual-tree complex wavelet transform. Next, an improved local adaptive tone mapping method is applied to process the low frequency components of the image, and a soft threshold denoising algorithm is used to denoise the high frequency components of the image. Then, the V-channel is rebuilt and the contrast is adjusted using white balance method. Finally, the processed image is converted back into the RGB color space as the enhanced result. Experimental results show that the proposed method can effectively improve the performance in terms of contrast enhancement, noise reduction and color reproduction.</description><identifier>ISSN: 1673-1905</identifier><identifier>EISSN: 1993-5013</identifier><identifier>DOI: 10.1007/s11801-018-8046-5</identifier><language>eng</language><publisher>Tianjin: Tianjin University of Technology</publisher><subject>Color ; Image contrast ; Image enhancement ; Lasers ; Mapping ; Noise reduction ; Optical Devices ; Optics ; Performance enhancement ; Photonics ; Physics ; Physics and Astronomy ; Retinex (algorithm) ; Wavelet transforms ; White balancing</subject><ispartof>Optoelectronics letters, 2018-11, Vol.14 (6), p.470-475</ispartof><rights>Tianjin University of Technology and Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>Copyright Springer Science & Business Media 2018</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-68b864fd39eddb3640845456a5f3332fd44553e13b492113f5831556400c9193</citedby><cites>FETCH-LOGICAL-c316t-68b864fd39eddb3640845456a5f3332fd44553e13b492113f5831556400c9193</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11801-018-8046-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11801-018-8046-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Yang, Mao-xiang</creatorcontrib><creatorcontrib>Tang, Gui-jin</creatorcontrib><creatorcontrib>Liu, Xiao-hua</creatorcontrib><creatorcontrib>Wang, Li-qian</creatorcontrib><creatorcontrib>Cui, Zi-guan</creatorcontrib><creatorcontrib>Luo, Su-huai</creatorcontrib><title>Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform</title><title>Optoelectronics letters</title><addtitle>Optoelectron. Lett</addtitle><description>In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform (DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-channel by dual-tree complex wavelet transform. Next, an improved local adaptive tone mapping method is applied to process the low frequency components of the image, and a soft threshold denoising algorithm is used to denoise the high frequency components of the image. Then, the V-channel is rebuilt and the contrast is adjusted using white balance method. Finally, the processed image is converted back into the RGB color space as the enhanced result. Experimental results show that the proposed method can effectively improve the performance in terms of contrast enhancement, noise reduction and color reproduction.</description><subject>Color</subject><subject>Image contrast</subject><subject>Image enhancement</subject><subject>Lasers</subject><subject>Mapping</subject><subject>Noise reduction</subject><subject>Optical Devices</subject><subject>Optics</subject><subject>Performance enhancement</subject><subject>Photonics</subject><subject>Physics</subject><subject>Physics and Astronomy</subject><subject>Retinex (algorithm)</subject><subject>Wavelet transforms</subject><subject>White balancing</subject><issn>1673-1905</issn><issn>1993-5013</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LAzEQhoMoWLQ_wFvAczSzSXaToxS_oCBIbx5Cdne2H2yzNUmt_femrODJuczAvO87zEPIDfA74Ly6jwCaA-OgmeayZOqMTMAYwRQHcZ7nshIMDFeXZBrjhucSRaWlmZCP-XBg_Xq5SnS9dUuk6FfON7hFn2jtIrZ08PQd09rjN00rHMKROt_Sdu96lgIibYbtrs_Lg_vCHhNNwfnYDWF7TS4610ec_vYrsnh6XMxe2Pzt-XX2MGeNgDKxUte6lF0rDLZtLUrJtVRSlU51Qoiia6VUSiCIWpoCQHRKC1Aq63hjwIgrcjvG7sLwuceY7GbYB58v2gKkMSoHVlkFo6oJQ4wBO7sL-eNwtMDtiaIdKdpM0Z4oWpU9xeiJWeuXGP6S_zf9AGXsc2I</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Yang, Mao-xiang</creator><creator>Tang, Gui-jin</creator><creator>Liu, Xiao-hua</creator><creator>Wang, Li-qian</creator><creator>Cui, Zi-guan</creator><creator>Luo, Su-huai</creator><general>Tianjin University of Technology</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20181101</creationdate><title>Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform</title><author>Yang, Mao-xiang ; Tang, Gui-jin ; Liu, Xiao-hua ; Wang, Li-qian ; Cui, Zi-guan ; Luo, Su-huai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-68b864fd39eddb3640845456a5f3332fd44553e13b492113f5831556400c9193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Color</topic><topic>Image contrast</topic><topic>Image enhancement</topic><topic>Lasers</topic><topic>Mapping</topic><topic>Noise reduction</topic><topic>Optical Devices</topic><topic>Optics</topic><topic>Performance enhancement</topic><topic>Photonics</topic><topic>Physics</topic><topic>Physics and Astronomy</topic><topic>Retinex (algorithm)</topic><topic>Wavelet transforms</topic><topic>White balancing</topic><toplevel>online_resources</toplevel><creatorcontrib>Yang, Mao-xiang</creatorcontrib><creatorcontrib>Tang, Gui-jin</creatorcontrib><creatorcontrib>Liu, Xiao-hua</creatorcontrib><creatorcontrib>Wang, Li-qian</creatorcontrib><creatorcontrib>Cui, Zi-guan</creatorcontrib><creatorcontrib>Luo, Su-huai</creatorcontrib><collection>CrossRef</collection><jtitle>Optoelectronics letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Mao-xiang</au><au>Tang, Gui-jin</au><au>Liu, Xiao-hua</au><au>Wang, Li-qian</au><au>Cui, Zi-guan</au><au>Luo, Su-huai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform</atitle><jtitle>Optoelectronics letters</jtitle><stitle>Optoelectron. Lett</stitle><date>2018-11-01</date><risdate>2018</risdate><volume>14</volume><issue>6</issue><spage>470</spage><epage>475</epage><pages>470-475</pages><issn>1673-1905</issn><eissn>1993-5013</eissn><abstract>In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform (DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-channel by dual-tree complex wavelet transform. Next, an improved local adaptive tone mapping method is applied to process the low frequency components of the image, and a soft threshold denoising algorithm is used to denoise the high frequency components of the image. Then, the V-channel is rebuilt and the contrast is adjusted using white balance method. Finally, the processed image is converted back into the RGB color space as the enhanced result. Experimental results show that the proposed method can effectively improve the performance in terms of contrast enhancement, noise reduction and color reproduction.</abstract><cop>Tianjin</cop><pub>Tianjin University of Technology</pub><doi>10.1007/s11801-018-8046-5</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1673-1905 |
| ispartof | Optoelectronics letters, 2018-11, Vol.14 (6), p.470-475 |
| issn | 1673-1905 1993-5013 |
| language | eng |
| recordid | cdi_proquest_journals_2149954087 |
| source | SpringerLink Journals; Alma/SFX Local Collection |
| subjects | Color Image contrast Image enhancement Lasers Mapping Noise reduction Optical Devices Optics Performance enhancement Photonics Physics Physics and Astronomy Retinex (algorithm) Wavelet transforms White balancing |
| title | Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T03%3A53%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Low-light%20image%20enhancement%20based%20on%20Retinex%20theory%20and%20dual-tree%20complex%20wavelet%20transform&rft.jtitle=Optoelectronics%20letters&rft.au=Yang,%20Mao-xiang&rft.date=2018-11-01&rft.volume=14&rft.issue=6&rft.spage=470&rft.epage=475&rft.pages=470-475&rft.issn=1673-1905&rft.eissn=1993-5013&rft_id=info:doi/10.1007/s11801-018-8046-5&rft_dat=%3Cproquest_cross%3E2149954087%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2149954087&rft_id=info:pmid/&rfr_iscdi=true |