{"title":"天气退化图像导数的遮挡边缘检测","authors":"Daniel Lévesque, F. Deschênes","doi":"10.1109/CRV.2005.35","DOIUrl":null,"url":null,"abstract":"Degradation of images of outdoor scenes caused by varying conditions of visibility can be exploited in order to get information on the scene. We propose two new methods for detecting occlusion edges between textured areas of a scene. These methods are based on the use of partial derivatives of two images acquired under different conditions of visibility. They were validated on images of both synthetic and real scenes.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Detection of occlusion edges from the derivatives of weather degraded images\",\"authors\":\"Daniel Lévesque, F. Deschênes\",\"doi\":\"10.1109/CRV.2005.35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Degradation of images of outdoor scenes caused by varying conditions of visibility can be exploited in order to get information on the scene. We propose two new methods for detecting occlusion edges between textured areas of a scene. These methods are based on the use of partial derivatives of two images acquired under different conditions of visibility. They were validated on images of both synthetic and real scenes.\",\"PeriodicalId\":307318,\"journal\":{\"name\":\"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2005.35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2005.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of occlusion edges from the derivatives of weather degraded images
Degradation of images of outdoor scenes caused by varying conditions of visibility can be exploited in order to get information on the scene. We propose two new methods for detecting occlusion edges between textured areas of a scene. These methods are based on the use of partial derivatives of two images acquired under different conditions of visibility. They were validated on images of both synthetic and real scenes.
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