{"title":"一个统计统一的图像插值，误差隐藏，和源适应滤波器设计","authors":"M. Muhlich, R. Mester","doi":"10.1109/IAI.2004.1300959","DOIUrl":null,"url":null,"abstract":"The natural characteristics of image signals and the statistics of measurement noise are decisive for designing optimal filter sets and optimal estimation methods in signal processing. Astonishingly, this principle has so far only partially found its way into the field of image sequence processing. We show how a Wiener-type MMSE optimization criterion for the resulting image signal, based on a simple covariance model of images or image sequences, provides direct and intelligible solutions for various, apparently different, problems, such as error concealment, or adaption of filters to signal and noise statistics.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A statistical unification of image interpolation, error concealment, and source-adapted filter design\",\"authors\":\"M. Muhlich, R. Mester\",\"doi\":\"10.1109/IAI.2004.1300959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The natural characteristics of image signals and the statistics of measurement noise are decisive for designing optimal filter sets and optimal estimation methods in signal processing. Astonishingly, this principle has so far only partially found its way into the field of image sequence processing. We show how a Wiener-type MMSE optimization criterion for the resulting image signal, based on a simple covariance model of images or image sequences, provides direct and intelligible solutions for various, apparently different, problems, such as error concealment, or adaption of filters to signal and noise statistics.\",\"PeriodicalId\":326040,\"journal\":{\"name\":\"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI.2004.1300959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI.2004.1300959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A statistical unification of image interpolation, error concealment, and source-adapted filter design
The natural characteristics of image signals and the statistics of measurement noise are decisive for designing optimal filter sets and optimal estimation methods in signal processing. Astonishingly, this principle has so far only partially found its way into the field of image sequence processing. We show how a Wiener-type MMSE optimization criterion for the resulting image signal, based on a simple covariance model of images or image sequences, provides direct and intelligible solutions for various, apparently different, problems, such as error concealment, or adaption of filters to signal and noise statistics.
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