I. Stephanakis, G. Anastassopoulos, A. Karayiannakis, C. Simopoulos
{"title":"Enhancement of medical images using a fuzzy model for segment dependent local equalization","authors":"I. Stephanakis, G. Anastassopoulos, A. Karayiannakis, C. Simopoulos","doi":"10.1109/ISPA.2003.1296420","DOIUrl":null,"url":null,"abstract":"A novel model for fuzzy equalization of medical images is proposed. The method requires a preprocessing step which accomplishes a fuzzy segmentation of the image into N segments with overlapping fuzzy boundaries. Histogram equalization is performed according to individual equalization functions derived from each segment of the image. A fuzzy membership function is associated with each segment. Enhancement results compare well against histogram equalization techniques that derive the equalization transform function from the global histogram of the image.","PeriodicalId":218932,"journal":{"name":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","volume":"207 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2003.1296420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
A novel model for fuzzy equalization of medical images is proposed. The method requires a preprocessing step which accomplishes a fuzzy segmentation of the image into N segments with overlapping fuzzy boundaries. Histogram equalization is performed according to individual equalization functions derived from each segment of the image. A fuzzy membership function is associated with each segment. Enhancement results compare well against histogram equalization techniques that derive the equalization transform function from the global histogram of the image.