{"title":"第十五章:灰度图像和彩色图像的中值绝对偏差估计","authors":"H. H. Khalil, R. Rahmat, W. A. Mahmoud","doi":"10.1109/GMAI.2008.7","DOIUrl":null,"url":null,"abstract":"This paper presents a new algorithm for estimation of noise (i.e., level of noise) in both gray-scale and color images (GSI, CI). The new technique is called median-absolute deviation (MAD). This technique does require an explicit estimation of the noise level or the signal to noise ratio (SNR), which is usually needed in most of the popular enhancement methods. Performance of the proposed method is evaluated on noisy images in real conditions and with artificial noise.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Chapter 15: Estimation of Noise in Gray-Scale and Colored Images Using Median Absolute Deviation (MAD)\",\"authors\":\"H. H. Khalil, R. Rahmat, W. A. Mahmoud\",\"doi\":\"10.1109/GMAI.2008.7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new algorithm for estimation of noise (i.e., level of noise) in both gray-scale and color images (GSI, CI). The new technique is called median-absolute deviation (MAD). This technique does require an explicit estimation of the noise level or the signal to noise ratio (SNR), which is usually needed in most of the popular enhancement methods. Performance of the proposed method is evaluated on noisy images in real conditions and with artificial noise.\",\"PeriodicalId\":393559,\"journal\":{\"name\":\"2008 3rd International Conference on Geometric Modeling and Imaging\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 3rd International Conference on Geometric Modeling and Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GMAI.2008.7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 3rd International Conference on Geometric Modeling and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GMAI.2008.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chapter 15: Estimation of Noise in Gray-Scale and Colored Images Using Median Absolute Deviation (MAD)
This paper presents a new algorithm for estimation of noise (i.e., level of noise) in both gray-scale and color images (GSI, CI). The new technique is called median-absolute deviation (MAD). This technique does require an explicit estimation of the noise level or the signal to noise ratio (SNR), which is usually needed in most of the popular enhancement methods. Performance of the proposed method is evaluated on noisy images in real conditions and with artificial noise.
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