{"title":"通过熵产生增强图像对比度","authors":"Mario Ferraro , Giuseppe Boccignone","doi":"10.1016/j.rti.2004.05.004","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper a novel approach for image contrast enhancement is proposed. Employing a thermodynamical model to define local information content, the method derives a measure of local contrast which takes into account spatial structure across multiple scales. From this measure a local contrast map is computed, which is then applied to the image, giving rise to a selective enhancement of the original image. Here some applications to medical images will be presented as well as a comparison with other methods.</p></div>","PeriodicalId":101062,"journal":{"name":"Real-Time Imaging","volume":"10 4","pages":"Pages 229-238"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.rti.2004.05.004","citationCount":"7","resultStr":"{\"title\":\"Image contrast enhancement via entropy production\",\"authors\":\"Mario Ferraro , Giuseppe Boccignone\",\"doi\":\"10.1016/j.rti.2004.05.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper a novel approach for image contrast enhancement is proposed. Employing a thermodynamical model to define local information content, the method derives a measure of local contrast which takes into account spatial structure across multiple scales. From this measure a local contrast map is computed, which is then applied to the image, giving rise to a selective enhancement of the original image. Here some applications to medical images will be presented as well as a comparison with other methods.</p></div>\",\"PeriodicalId\":101062,\"journal\":{\"name\":\"Real-Time Imaging\",\"volume\":\"10 4\",\"pages\":\"Pages 229-238\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.rti.2004.05.004\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Real-Time Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1077201404000440\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Real-Time Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077201404000440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper a novel approach for image contrast enhancement is proposed. Employing a thermodynamical model to define local information content, the method derives a measure of local contrast which takes into account spatial structure across multiple scales. From this measure a local contrast map is computed, which is then applied to the image, giving rise to a selective enhancement of the original image. Here some applications to medical images will be presented as well as a comparison with other methods.