{"title":"基于一致分割的粗配准图像颜色校正","authors":"Haoxing Wang, Longquan Dai, Xiaopeng Zhang","doi":"10.1109/ACPR.2013.72","DOIUrl":null,"url":null,"abstract":"Local color correction methods transfer colors between corresponding regions. However, inconsistent segmentation between the source image and the target image tends to degrade the correction result. In this paper, we propose a local color correction technique for coarsely registered images. In the segmentation step, it enforces the consistent segmentation on both source and target images to alleviate the inaccurate registration problem. In the color transfer step, it uses the region confidences and the bilateral-filter-like color influence maps to improve the color correction result. The experiment shows the proposed method achieves improved color correction results compared with the global methods and the recent local color correction methods.","PeriodicalId":365633,"journal":{"name":"2013 2nd IAPR Asian Conference on Pattern Recognition","volume":"22 3 Suppl 7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Consistent Segmentation Based Color Correction for Coarsely Registered Images\",\"authors\":\"Haoxing Wang, Longquan Dai, Xiaopeng Zhang\",\"doi\":\"10.1109/ACPR.2013.72\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Local color correction methods transfer colors between corresponding regions. However, inconsistent segmentation between the source image and the target image tends to degrade the correction result. In this paper, we propose a local color correction technique for coarsely registered images. In the segmentation step, it enforces the consistent segmentation on both source and target images to alleviate the inaccurate registration problem. In the color transfer step, it uses the region confidences and the bilateral-filter-like color influence maps to improve the color correction result. The experiment shows the proposed method achieves improved color correction results compared with the global methods and the recent local color correction methods.\",\"PeriodicalId\":365633,\"journal\":{\"name\":\"2013 2nd IAPR Asian Conference on Pattern Recognition\",\"volume\":\"22 3 Suppl 7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 2nd IAPR Asian Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACPR.2013.72\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 2nd IAPR Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2013.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Consistent Segmentation Based Color Correction for Coarsely Registered Images
Local color correction methods transfer colors between corresponding regions. However, inconsistent segmentation between the source image and the target image tends to degrade the correction result. In this paper, we propose a local color correction technique for coarsely registered images. In the segmentation step, it enforces the consistent segmentation on both source and target images to alleviate the inaccurate registration problem. In the color transfer step, it uses the region confidences and the bilateral-filter-like color influence maps to improve the color correction result. The experiment shows the proposed method achieves improved color correction results compared with the global methods and the recent local color correction methods.