No Reference Uneven Illumination Assessment for Dermoscopy Images
For the dermoscopy image, uneven illumination will influence segmentation accuracy and lead to wrong aided diagnosis result. In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted image is decomposed to illumination and reflectan...
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| Veröffentlicht in: | IEEE signal processing letters 2015-05, Vol.22 (5), p.534-538 |
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| container_title | IEEE signal processing letters |
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| creator | Lu, Yanan Xie, Fengying Wu, Yefen Jiang, Zhiguo Meng, Rusong |
| description | For the dermoscopy image, uneven illumination will influence segmentation accuracy and lead to wrong aided diagnosis result. In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted image is decomposed to illumination and reflectance components through variational framework for Retinex (VFR). Then, the illumination component is extracted by basis function fitting. Lastly, average gradient of the illumination component (AGIC) is calculated as the uneven illumination metric. A series of experiments show that, the proposed illumination extraction method is insensitive to the image content, and the proposed metric delivers an accurate illumination assessment result. |
| doi_str_mv | 10.1109/LSP.2014.2357015 |
| format | Article |
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In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted image is decomposed to illumination and reflectance components through variational framework for Retinex (VFR). Then, the illumination component is extracted by basis function fitting. Lastly, average gradient of the illumination component (AGIC) is calculated as the uneven illumination metric. A series of experiments show that, the proposed illumination extraction method is insensitive to the image content, and the proposed metric delivers an accurate illumination assessment result.</description><identifier>ISSN: 1070-9908</identifier><identifier>EISSN: 1558-2361</identifier><identifier>DOI: 10.1109/LSP.2014.2357015</identifier><identifier>CODEN: ISPLEM</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Assessments ; Dermoscopy ; Distortion ; Illumination ; image quality assessment (IQA) ; Lighting ; Mathematical analysis ; Measurement ; no reference ; Nonlinear distortion ; Reflectivity ; Retinex (algorithm) ; Segmentation ; Signal processing algorithms ; Transform coding ; uneven illumination</subject><ispartof>IEEE signal processing letters, 2015-05, Vol.22 (5), p.534-538</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c296t-88c037ff206724d8968bfce737dac72424306896904c404ee6009b229bbfea463</citedby><cites>FETCH-LOGICAL-c296t-88c037ff206724d8968bfce737dac72424306896904c404ee6009b229bbfea463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6895294$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6895294$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lu, Yanan</creatorcontrib><creatorcontrib>Xie, Fengying</creatorcontrib><creatorcontrib>Wu, Yefen</creatorcontrib><creatorcontrib>Jiang, Zhiguo</creatorcontrib><creatorcontrib>Meng, Rusong</creatorcontrib><title>No Reference Uneven Illumination Assessment for Dermoscopy Images</title><title>IEEE signal processing letters</title><addtitle>LSP</addtitle><description>For the dermoscopy image, uneven illumination will influence segmentation accuracy and lead to wrong aided diagnosis result. In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted image is decomposed to illumination and reflectance components through variational framework for Retinex (VFR). Then, the illumination component is extracted by basis function fitting. Lastly, average gradient of the illumination component (AGIC) is calculated as the uneven illumination metric. A series of experiments show that, the proposed illumination extraction method is insensitive to the image content, and the proposed metric delivers an accurate illumination assessment result.</description><subject>Algorithm design and analysis</subject><subject>Assessments</subject><subject>Dermoscopy</subject><subject>Distortion</subject><subject>Illumination</subject><subject>image quality assessment (IQA)</subject><subject>Lighting</subject><subject>Mathematical analysis</subject><subject>Measurement</subject><subject>no reference</subject><subject>Nonlinear distortion</subject><subject>Reflectivity</subject><subject>Retinex (algorithm)</subject><subject>Segmentation</subject><subject>Signal processing algorithms</subject><subject>Transform coding</subject><subject>uneven illumination</subject><issn>1070-9908</issn><issn>1558-2361</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1LAzEQxYMoWKt3wcsevWydZLPZ5FjqV2FRUXsOu-lEVnaTmmyF_vemtHia4fHeMO9HyDWFGaWg7uqPtxkDymesKCug5QmZ0LKUOSsEPU07VJArBfKcXMT4DQCSynJC5i8-e0eLAZ3BbOXwF1227Pvt0Llm7LzL5jFijAO6MbM-ZPcYBh-N3-yy5dB8YbwkZ7bpI14d55SsHh8-F895_fq0XMzr3DAlxlxKA0VlLQNRMb6WSsjWGqyKat2YpDBegEiqAm44cEQBoFrGVNtabLgopuT2cHcT_M8W46iHLhrs-8ah30ZNBWeM0VQ9WeFgNcHHGNDqTeiGJuw0Bb2npRMtvaelj7RS5OYQ6RDx354eKpnixR__dGTD</recordid><startdate>201505</startdate><enddate>201505</enddate><creator>Lu, Yanan</creator><creator>Xie, Fengying</creator><creator>Wu, Yefen</creator><creator>Jiang, Zhiguo</creator><creator>Meng, Rusong</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201505</creationdate><title>No Reference Uneven Illumination Assessment for Dermoscopy Images</title><author>Lu, Yanan ; Xie, Fengying ; Wu, Yefen ; Jiang, Zhiguo ; Meng, Rusong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c296t-88c037ff206724d8968bfce737dac72424306896904c404ee6009b229bbfea463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithm design and analysis</topic><topic>Assessments</topic><topic>Dermoscopy</topic><topic>Distortion</topic><topic>Illumination</topic><topic>image quality assessment (IQA)</topic><topic>Lighting</topic><topic>Mathematical analysis</topic><topic>Measurement</topic><topic>no reference</topic><topic>Nonlinear distortion</topic><topic>Reflectivity</topic><topic>Retinex (algorithm)</topic><topic>Segmentation</topic><topic>Signal processing algorithms</topic><topic>Transform coding</topic><topic>uneven illumination</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lu, Yanan</creatorcontrib><creatorcontrib>Xie, Fengying</creatorcontrib><creatorcontrib>Wu, Yefen</creatorcontrib><creatorcontrib>Jiang, Zhiguo</creatorcontrib><creatorcontrib>Meng, Rusong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE signal processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lu, Yanan</au><au>Xie, Fengying</au><au>Wu, Yefen</au><au>Jiang, Zhiguo</au><au>Meng, Rusong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>No Reference Uneven Illumination Assessment for Dermoscopy Images</atitle><jtitle>IEEE signal processing letters</jtitle><stitle>LSP</stitle><date>2015-05</date><risdate>2015</risdate><volume>22</volume><issue>5</issue><spage>534</spage><epage>538</epage><pages>534-538</pages><issn>1070-9908</issn><eissn>1558-2361</eissn><coden>ISPLEM</coden><abstract>For the dermoscopy image, uneven illumination will influence segmentation accuracy and lead to wrong aided diagnosis result. In this paper, a no reference uneven illumination assessment metric is proposed for dermoscopy images. Firstly, the distorted image is decomposed to illumination and reflectance components through variational framework for Retinex (VFR). Then, the illumination component is extracted by basis function fitting. Lastly, average gradient of the illumination component (AGIC) is calculated as the uneven illumination metric. A series of experiments show that, the proposed illumination extraction method is insensitive to the image content, and the proposed metric delivers an accurate illumination assessment result.</abstract><pub>IEEE</pub><doi>10.1109/LSP.2014.2357015</doi><tpages>5</tpages></addata></record> |
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| ispartof | IEEE signal processing letters, 2015-05, Vol.22 (5), p.534-538 |
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| subjects | Algorithm design and analysis Assessments Dermoscopy Distortion Illumination image quality assessment (IQA) Lighting Mathematical analysis Measurement no reference Nonlinear distortion Reflectivity Retinex (algorithm) Segmentation Signal processing algorithms Transform coding uneven illumination |
| title | No Reference Uneven Illumination Assessment for Dermoscopy Images |
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