{"title":"纹理表面上高光反射的分离","authors":"P. Tan, Long Quan, Stephen Lin","doi":"10.1109/CVPR.2006.273","DOIUrl":null,"url":null,"abstract":"We present a method for separating highlight reflections on textured surfaces. In contrast to previous techniques that use diffuse color information from outside the highlight area to constrain the solution, the proposed method further capitalizes on the spatial distributions of colors to resolve ambiguities in separation that often arise in real images. For highlight pixels in which a clear-cut separation cannot be determined from color space analysis, we evaluate possible separation solutions based on their consistency with diffuse texture characteristics outside the highlight. With consideration of color distributions in both the color space and the image space, appreciably enhanced separation performance can be attained in challenging cases.","PeriodicalId":421737,"journal":{"name":"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":"{\"title\":\"Separation of Highlight Reflections on Textured Surfaces\",\"authors\":\"P. Tan, Long Quan, Stephen Lin\",\"doi\":\"10.1109/CVPR.2006.273\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a method for separating highlight reflections on textured surfaces. In contrast to previous techniques that use diffuse color information from outside the highlight area to constrain the solution, the proposed method further capitalizes on the spatial distributions of colors to resolve ambiguities in separation that often arise in real images. For highlight pixels in which a clear-cut separation cannot be determined from color space analysis, we evaluate possible separation solutions based on their consistency with diffuse texture characteristics outside the highlight. With consideration of color distributions in both the color space and the image space, appreciably enhanced separation performance can be attained in challenging cases.\",\"PeriodicalId\":421737,\"journal\":{\"name\":\"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"58\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.2006.273\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.2006.273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Separation of Highlight Reflections on Textured Surfaces
We present a method for separating highlight reflections on textured surfaces. In contrast to previous techniques that use diffuse color information from outside the highlight area to constrain the solution, the proposed method further capitalizes on the spatial distributions of colors to resolve ambiguities in separation that often arise in real images. For highlight pixels in which a clear-cut separation cannot be determined from color space analysis, we evaluate possible separation solutions based on their consistency with diffuse texture characteristics outside the highlight. With consideration of color distributions in both the color space and the image space, appreciably enhanced separation performance can be attained in challenging cases.