{"title":"噪声失焦模糊图像复原中的点扩散函数估计","authors":"Xue-fen Wan, Yi Yang, Xin Lin","doi":"10.1109/ICSESS.2010.5552448","DOIUrl":null,"url":null,"abstract":"An analysis about point spread function estimation and image clarity evaluation about high-noise out-of-focus blurred image is present. The geometry and spline interpolating solving method are used for point spread function analysis. The FIR filter is adopted to provide low-fluctuating curve for interpolation. Three kinds of image clarity evaluation function are compared for iterative arithmetic selecting and results show that the methods based on Laplace transform of the image is preferred. Experimental results confirm this evaluation method is applicable for high-noise blurred image restoration.","PeriodicalId":264630,"journal":{"name":"2010 IEEE International Conference on Software Engineering and Service Sciences","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Point spread function estimation for noisy out-of-focus blur image restoration\",\"authors\":\"Xue-fen Wan, Yi Yang, Xin Lin\",\"doi\":\"10.1109/ICSESS.2010.5552448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An analysis about point spread function estimation and image clarity evaluation about high-noise out-of-focus blurred image is present. The geometry and spline interpolating solving method are used for point spread function analysis. The FIR filter is adopted to provide low-fluctuating curve for interpolation. Three kinds of image clarity evaluation function are compared for iterative arithmetic selecting and results show that the methods based on Laplace transform of the image is preferred. Experimental results confirm this evaluation method is applicable for high-noise blurred image restoration.\",\"PeriodicalId\":264630,\"journal\":{\"name\":\"2010 IEEE International Conference on Software Engineering and Service Sciences\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Software Engineering and Service Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2010.5552448\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Software Engineering and Service Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2010.5552448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Point spread function estimation for noisy out-of-focus blur image restoration
An analysis about point spread function estimation and image clarity evaluation about high-noise out-of-focus blurred image is present. The geometry and spline interpolating solving method are used for point spread function analysis. The FIR filter is adopted to provide low-fluctuating curve for interpolation. Three kinds of image clarity evaluation function are compared for iterative arithmetic selecting and results show that the methods based on Laplace transform of the image is preferred. Experimental results confirm this evaluation method is applicable for high-noise blurred image restoration.