A. Bosco, Davide Giacalone, A. Bruna, S. Battiato, Rosetta Rizzo
{"title":"原始数字图像中内置噪声管理的信号活动估计","authors":"A. Bosco, Davide Giacalone, A. Bruna, S. Battiato, Rosetta Rizzo","doi":"10.5220/0004280301180121","DOIUrl":null,"url":null,"abstract":"Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Signal Activity Estimation with Built-in Noise Management in Raw Digital Images\",\"authors\":\"A. Bosco, Davide Giacalone, A. Bruna, S. Battiato, Rosetta Rizzo\",\"doi\":\"10.5220/0004280301180121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.\",\"PeriodicalId\":411140,\"journal\":{\"name\":\"International Conference on Computer Vision Theory and Applications\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computer Vision Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0004280301180121\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computer Vision Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0004280301180121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Signal Activity Estimation with Built-in Noise Management in Raw Digital Images
Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.