{"title":"色兔:在照明估计中引导局部最大值的距离","authors":"Nikola Banić, S. Lončarić","doi":"10.1109/ICDSP.2014.6900684","DOIUrl":null,"url":null,"abstract":"In this paper the Color Rabbit (CR), a new low-level statistics-based color constancy algorithm for illumination estimation is proposed and tested. Based on the Color Sparrow (CS) algorithm it combines multiple local illumination estimations found by using a new approach into a global one. The algorithm is tested on several publicly available color constancy databases and it outperforms almost all other color constancy algorithms in terms of accuracy and execution speed.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Color Rabbit: Guiding the distance of local maximums in illumination estimation\",\"authors\":\"Nikola Banić, S. Lončarić\",\"doi\":\"10.1109/ICDSP.2014.6900684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the Color Rabbit (CR), a new low-level statistics-based color constancy algorithm for illumination estimation is proposed and tested. Based on the Color Sparrow (CS) algorithm it combines multiple local illumination estimations found by using a new approach into a global one. The algorithm is tested on several publicly available color constancy databases and it outperforms almost all other color constancy algorithms in terms of accuracy and execution speed.\",\"PeriodicalId\":301856,\"journal\":{\"name\":\"2014 19th International Conference on Digital Signal Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 19th International Conference on Digital Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSP.2014.6900684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 19th International Conference on Digital Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2014.6900684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Color Rabbit: Guiding the distance of local maximums in illumination estimation
In this paper the Color Rabbit (CR), a new low-level statistics-based color constancy algorithm for illumination estimation is proposed and tested. Based on the Color Sparrow (CS) algorithm it combines multiple local illumination estimations found by using a new approach into a global one. The algorithm is tested on several publicly available color constancy databases and it outperforms almost all other color constancy algorithms in terms of accuracy and execution speed.
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