脱色:rgb2gray()脱色了吗?

Yibing Song, Linchao Bao, Xiaobin Xu, Qingxiong Yang
{"title":"脱色:rgb2gray()脱色了吗?","authors":"Yibing Song, Linchao Bao, Xiaobin Xu, Qingxiong Yang","doi":"10.1145/2542355.2542374","DOIUrl":null,"url":null,"abstract":"Decolorization problems originate from the fact that the luminance channel may fail to represent iso-luminant regions in the original color image. Currently all the existing methods suffer from the same weakness -- robustness: failure cases can be easily found for each of the methods. This prevents all these methods from being practical for real-world applications. In fact, the luminance conversion (i.e, rgb2gray() function in Matlab) performs rather well in practice only with exceptions for failure cases like the iso-luminant regions. Thus a thought-provoking question is naturally raised: can we reach a robust solution by simply modifying the rgb2gray() to avoid failures in iso-luminant regions? Instead of assigning fixed channel weights for all images, a more flexible strategy would be choosing channel weights depending on specific images to avoid indiscrimination in iso-luminant regions. Following this strategy, by considering multi-scale contrast preservation, we design an algorithm that can consistently produce \"good\" results for each color image, among which the \"best\" one preferred by users can be selected by further involving perceptual contrasts preferences. The results are verified through user study.","PeriodicalId":232593,"journal":{"name":"SIGGRAPH Asia 2013 Technical Briefs","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"Decolorization: is rgb2gray() out?\",\"authors\":\"Yibing Song, Linchao Bao, Xiaobin Xu, Qingxiong Yang\",\"doi\":\"10.1145/2542355.2542374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decolorization problems originate from the fact that the luminance channel may fail to represent iso-luminant regions in the original color image. Currently all the existing methods suffer from the same weakness -- robustness: failure cases can be easily found for each of the methods. This prevents all these methods from being practical for real-world applications. In fact, the luminance conversion (i.e, rgb2gray() function in Matlab) performs rather well in practice only with exceptions for failure cases like the iso-luminant regions. Thus a thought-provoking question is naturally raised: can we reach a robust solution by simply modifying the rgb2gray() to avoid failures in iso-luminant regions? Instead of assigning fixed channel weights for all images, a more flexible strategy would be choosing channel weights depending on specific images to avoid indiscrimination in iso-luminant regions. Following this strategy, by considering multi-scale contrast preservation, we design an algorithm that can consistently produce \\\"good\\\" results for each color image, among which the \\\"best\\\" one preferred by users can be selected by further involving perceptual contrasts preferences. The results are verified through user study.\",\"PeriodicalId\":232593,\"journal\":{\"name\":\"SIGGRAPH Asia 2013 Technical Briefs\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH Asia 2013 Technical Briefs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2542355.2542374\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGGRAPH Asia 2013 Technical Briefs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2542355.2542374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44

摘要

脱色问题源于亮度通道可能无法表示原始彩色图像中的等亮度区域。目前,所有现有的方法都有一个共同的弱点——鲁棒性:每种方法都很容易找到失败的案例。这使得所有这些方法在实际应用中都不实用。事实上,亮度转换(即Matlab中的rgb2gray()函数)在实践中表现相当好,只有在等亮度区域等失败情况下才会出现例外。因此,一个发人深省的问题自然被提出:我们能否通过简单地修改rgb2gray()来达到一个健壮的解决方案,以避免在等发光区域失败?而不是为所有图像分配固定的通道权重,一个更灵活的策略是根据特定的图像选择通道权重,以避免在等亮度区域的不区分。在此策略下,通过考虑多尺度对比度保存,我们设计了一种算法,可以对每个彩色图像始终产生“好”的结果,其中通过进一步涉及感知对比度偏好,可以选择用户喜欢的“最佳”结果。通过用户研究验证了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decolorization: is rgb2gray() out?
Decolorization problems originate from the fact that the luminance channel may fail to represent iso-luminant regions in the original color image. Currently all the existing methods suffer from the same weakness -- robustness: failure cases can be easily found for each of the methods. This prevents all these methods from being practical for real-world applications. In fact, the luminance conversion (i.e, rgb2gray() function in Matlab) performs rather well in practice only with exceptions for failure cases like the iso-luminant regions. Thus a thought-provoking question is naturally raised: can we reach a robust solution by simply modifying the rgb2gray() to avoid failures in iso-luminant regions? Instead of assigning fixed channel weights for all images, a more flexible strategy would be choosing channel weights depending on specific images to avoid indiscrimination in iso-luminant regions. Following this strategy, by considering multi-scale contrast preservation, we design an algorithm that can consistently produce "good" results for each color image, among which the "best" one preferred by users can be selected by further involving perceptual contrasts preferences. The results are verified through user study.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信