Detail enhancement decolorization algorithm based on rolling guided filtering
An important goal of color image gray-scale is to keep the edge details of the original color image as much as possible. In many cases, the degree of feature discrimination is maintained, but in some cases, edge details are still lost or blurred. Therefore, this paper first uses an improved non-line...
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| Veröffentlicht in: | Multimedia tools and applications 2022, Vol.81 (2), p.2711-2731 |
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| creator | Yu, Nana Li, Jinjiang Hua, Zhen |
| description | An important goal of color image gray-scale is to keep the edge details of the original color image as much as possible. In many cases, the degree of feature discrimination is maintained, but in some cases, edge details are still lost or blurred. Therefore, this paper first uses an improved non-linear global mapping grayscale method to grayscale the color image, and then proposes a grayscale image detail enhancement algorithm based on rolling guided filtering. The method in this paper is to enhance the edge details of the grayscale image by rolling guided filter processing on the basis of the grayscale image. In addition, the rolling-guided filter is a local linear model with better edge retention characteristics, which can overcome the defect that other filters are prone to gradient flips on the edges where the gray level of the image changes sharply, causing the image to appear “false edges”. The experimental results show that when the traditional method loses or blurs the detailed features, the method in this paper can maintain better detailed features. |
| doi_str_mv | 10.1007/s11042-021-11677-3 |
| format | Article |
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In many cases, the degree of feature discrimination is maintained, but in some cases, edge details are still lost or blurred. Therefore, this paper first uses an improved non-linear global mapping grayscale method to grayscale the color image, and then proposes a grayscale image detail enhancement algorithm based on rolling guided filtering. The method in this paper is to enhance the edge details of the grayscale image by rolling guided filter processing on the basis of the grayscale image. In addition, the rolling-guided filter is a local linear model with better edge retention characteristics, which can overcome the defect that other filters are prone to gradient flips on the edges where the gray level of the image changes sharply, causing the image to appear “false edges”. The experimental results show that when the traditional method loses or blurs the detailed features, the method in this paper can maintain better detailed features.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-021-11677-3</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Color imagery ; Computer Communication Networks ; Computer Science ; Data Structures and Information Theory ; Decoloring ; Gray scale ; Image enhancement ; Image filters ; Industrial production ; Information theory ; Multimedia ; Multimedia Information Systems ; Special Purpose and Application-Based Systems</subject><ispartof>Multimedia tools and applications, 2022, Vol.81 (2), p.2711-2731</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-af732df10b264b48841b509ac89d32f06c79a64219ab3708965204af99bd3a6b3</citedby><cites>FETCH-LOGICAL-c319t-af732df10b264b48841b509ac89d32f06c79a64219ab3708965204af99bd3a6b3</cites><orcidid>0000-0002-2080-8678</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-021-11677-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-021-11677-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Yu, Nana</creatorcontrib><creatorcontrib>Li, Jinjiang</creatorcontrib><creatorcontrib>Hua, Zhen</creatorcontrib><title>Detail enhancement decolorization algorithm based on rolling guided filtering</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>An important goal of color image gray-scale is to keep the edge details of the original color image as much as possible. 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In many cases, the degree of feature discrimination is maintained, but in some cases, edge details are still lost or blurred. Therefore, this paper first uses an improved non-linear global mapping grayscale method to grayscale the color image, and then proposes a grayscale image detail enhancement algorithm based on rolling guided filtering. The method in this paper is to enhance the edge details of the grayscale image by rolling guided filter processing on the basis of the grayscale image. In addition, the rolling-guided filter is a local linear model with better edge retention characteristics, which can overcome the defect that other filters are prone to gradient flips on the edges where the gray level of the image changes sharply, causing the image to appear “false edges”. 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| subjects | Algorithms Color imagery Computer Communication Networks Computer Science Data Structures and Information Theory Decoloring Gray scale Image enhancement Image filters Industrial production Information theory Multimedia Multimedia Information Systems Special Purpose and Application-Based Systems |
| title | Detail enhancement decolorization algorithm based on rolling guided filtering |
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