{"title":"基于混沌优化的x线图像增强","authors":"Yinjie Sun","doi":"10.1109/IWISA.2009.5072849","DOIUrl":null,"url":null,"abstract":"How to select the parameters of high-frequency emphasis filtering (HFEF) in order to enhance radiograph images, this paper presents an enhancing method based on chaos optimization algorithms (COA). Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. Firstly, an X-ray image is sharpened with HFEF, at the same time, the controllable and improved COA can optimize the parameters so that the optimal clarity of the image may be got, then the contrast of it is enhanced with histogram equalization to visually enhance the medical radiograph images to solve the questions: blurring and dark nature, which radiograph images generally tend to have. Experimental results show the proposed approach is effective and gets competitive visual effects.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"10 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Enhancement of Radiograph Images Based on Chaos Optimization\",\"authors\":\"Yinjie Sun\",\"doi\":\"10.1109/IWISA.2009.5072849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"How to select the parameters of high-frequency emphasis filtering (HFEF) in order to enhance radiograph images, this paper presents an enhancing method based on chaos optimization algorithms (COA). Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. Firstly, an X-ray image is sharpened with HFEF, at the same time, the controllable and improved COA can optimize the parameters so that the optimal clarity of the image may be got, then the contrast of it is enhanced with histogram equalization to visually enhance the medical radiograph images to solve the questions: blurring and dark nature, which radiograph images generally tend to have. Experimental results show the proposed approach is effective and gets competitive visual effects.\",\"PeriodicalId\":6327,\"journal\":{\"name\":\"2009 International Workshop on Intelligent Systems and Applications\",\"volume\":\"10 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2009.5072849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2009.5072849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancement of Radiograph Images Based on Chaos Optimization
How to select the parameters of high-frequency emphasis filtering (HFEF) in order to enhance radiograph images, this paper presents an enhancing method based on chaos optimization algorithms (COA). Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. Firstly, an X-ray image is sharpened with HFEF, at the same time, the controllable and improved COA can optimize the parameters so that the optimal clarity of the image may be got, then the contrast of it is enhanced with histogram equalization to visually enhance the medical radiograph images to solve the questions: blurring and dark nature, which radiograph images generally tend to have. Experimental results show the proposed approach is effective and gets competitive visual effects.