{"id":421002,"date":"2017-08-21T14:01:50","date_gmt":"2017-08-21T21:01:50","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=421002"},"modified":"2020-08-06T01:50:46","modified_gmt":"2020-08-06T08:50:46","slug":"separation-diffuse-specular-reflection-color-images","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/separation-diffuse-specular-reflection-color-images\/","title":{"rendered":"Separation of diffuse and specular reflection in color images"},"content":{"rendered":"<div id=\"LayoutWrapper\">\n<div class=\"ng-scope\">\n<div>\n<div class=\"pure-g document stats-document ng-isolate-scope\">\n<section class=\"tab-pane pure-u-1-1 u-printing-display-inline-ie u-printing-display-inline-ff\">\n<div class=\"ng-scope\">\n<div class=\"ng-scope\">\n<section id=\"990495\" class=\"pure-u-1-1 document-abstract document-tab u-p-2 ng-isolate-scope\">\n<div class=\"pure-g\">\n<div class=\"ng-scope pure-u-1-1\">\n<div class=\"ng-scope\">\n<div class=\"abstract-text ng-binding\">The presence of specular reflections in images can lead many traditional computer vision algorithms to produce erroneous results. To address this problem, we propose a method based on the neutral interface reflection model for separating the diffuse and specular reflection components in color images. From two photometric images without calibrated lighting, the illuminant chromaticity is estimated, and the RGB intensities of the two reflection components are computed for each pixel using a linear model of surface reflectance. Unlike most previous methods, the presented technique does not assume any dependencies among pixels, such as regionally uniform surface reflectance.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The presence of specular reflections in images can lead many traditional computer vision algorithms to produce erroneous results. To address this problem, we propose a method based on the neutral interface reflection model for separating the diffuse and specular reflection components in color images. From two photometric images without calibrated lighting, the illuminant chromaticity is [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Computer Vision and Pattern Recognition 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