{"title":"连接方法的自适应图像恢复算法","authors":"Ahmed Roukhe, Aziz Nachit","doi":"10.1016/S1251-8069(98)80036-5","DOIUrl":null,"url":null,"abstract":"<div><p>The analysis of brain operations allows us to build a computational model of an artificial neural network, able to restore gray level images degraded by a shiftinvariant blur function and additive noise. Our approach for restoration is carried out using a dynamic algorithm which minimizes an energy function. We show that it is not necessary to know the blur filter.</p></div>","PeriodicalId":100304,"journal":{"name":"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics-Physics-Chemistry-Astronomy","volume":"326 4","pages":"Pages 263-271"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1251-8069(98)80036-5","citationCount":"1","resultStr":"{\"title\":\"Algorithme adaptatif de restauration d'images par les méthodes connexionnistes\",\"authors\":\"Ahmed Roukhe, Aziz Nachit\",\"doi\":\"10.1016/S1251-8069(98)80036-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The analysis of brain operations allows us to build a computational model of an artificial neural network, able to restore gray level images degraded by a shiftinvariant blur function and additive noise. Our approach for restoration is carried out using a dynamic algorithm which minimizes an energy function. We show that it is not necessary to know the blur filter.</p></div>\",\"PeriodicalId\":100304,\"journal\":{\"name\":\"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics-Physics-Chemistry-Astronomy\",\"volume\":\"326 4\",\"pages\":\"Pages 263-271\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S1251-8069(98)80036-5\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics-Physics-Chemistry-Astronomy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1251806998800365\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics-Physics-Chemistry-Astronomy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1251806998800365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algorithme adaptatif de restauration d'images par les méthodes connexionnistes
The analysis of brain operations allows us to build a computational model of an artificial neural network, able to restore gray level images degraded by a shiftinvariant blur function and additive noise. Our approach for restoration is carried out using a dynamic algorithm which minimizes an energy function. We show that it is not necessary to know the blur filter.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
