{"title":"多分辨率图像的边缘保存","authors":"Ze-Nian Li, Gongzhu Hu","doi":"10.1016/1049-9652(92)90066-7","DOIUrl":null,"url":null,"abstract":"<div><p>Multiresolution image processing and analysis has become popular in recent years. One of the most important factors for the success of such systems is the preservation of edges in the process of producing images with reduced resolutions. In this paper 10 image reduction methods are introduced and a comparative evaluation is presented by using a set of synthetic test images and several real images. The quantitative evaluation employs an error measure based on normalized mean-square errors and a set of well-defined image parameters. Edge separation parameter is found to have a strikingly decisive impact on the edge preservation in the context of image reduction. Noise and edge width also show their significant effects. A normalized local intensity variance is studied to bridge the gap between the simple synthetic images and the real images. Finally, suitable methods for producing multiresolution images are recommended.</p></div>","PeriodicalId":100349,"journal":{"name":"CVGIP: Graphical Models and Image Processing","volume":"54 6","pages":"Pages 461-472"},"PeriodicalIF":0.0000,"publicationDate":"1992-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/1049-9652(92)90066-7","citationCount":"12","resultStr":"{\"title\":\"On edge preservation in multiresolution images\",\"authors\":\"Ze-Nian Li, Gongzhu Hu\",\"doi\":\"10.1016/1049-9652(92)90066-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Multiresolution image processing and analysis has become popular in recent years. One of the most important factors for the success of such systems is the preservation of edges in the process of producing images with reduced resolutions. In this paper 10 image reduction methods are introduced and a comparative evaluation is presented by using a set of synthetic test images and several real images. The quantitative evaluation employs an error measure based on normalized mean-square errors and a set of well-defined image parameters. Edge separation parameter is found to have a strikingly decisive impact on the edge preservation in the context of image reduction. Noise and edge width also show their significant effects. A normalized local intensity variance is studied to bridge the gap between the simple synthetic images and the real images. Finally, suitable methods for producing multiresolution images are recommended.</p></div>\",\"PeriodicalId\":100349,\"journal\":{\"name\":\"CVGIP: Graphical Models and Image Processing\",\"volume\":\"54 6\",\"pages\":\"Pages 461-472\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/1049-9652(92)90066-7\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CVGIP: Graphical Models and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/1049965292900667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CVGIP: Graphical Models and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/1049965292900667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiresolution image processing and analysis has become popular in recent years. One of the most important factors for the success of such systems is the preservation of edges in the process of producing images with reduced resolutions. In this paper 10 image reduction methods are introduced and a comparative evaluation is presented by using a set of synthetic test images and several real images. The quantitative evaluation employs an error measure based on normalized mean-square errors and a set of well-defined image parameters. Edge separation parameter is found to have a strikingly decisive impact on the edge preservation in the context of image reduction. Noise and edge width also show their significant effects. A normalized local intensity variance is studied to bridge the gap between the simple synthetic images and the real images. Finally, suitable methods for producing multiresolution images are recommended.