{"title":"基于模糊集和细分的图像增强方法","authors":"Guo Xian Jiu, Jiang Feng Jiao, L. Xiang","doi":"10.1109/ICAWST.2011.6163135","DOIUrl":null,"url":null,"abstract":"Alga microscopic image usually has a lot of noises and blurs. So a proper image enhancement algorithm which can remove noise and retain detail information is very important for alga microscopic image disposal. In the paper a new image enhancement method based on fuzzy set and subdivision is proposed. It is effective for alga microscopic image disposal. Subdivision scheme's good similarity among different subdivision layers makes the multi-resolution analysis has better approximation between the decomposed signals and the initial image. Subdivision method has strong ability to suppress noise through decomposing the initial image into low pass part. The image can be reconstructed through subdividing the low pass part of the initial image. Then the fuzzy set method is used for enhancement the reconstructed image. A special function is used as membership function in the process of fuzzification. The experimental results demonstrate the effectiveness of the proposed method for alga microscope image diaposal.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Image enhancement method based on fuzzy set and subdivision\",\"authors\":\"Guo Xian Jiu, Jiang Feng Jiao, L. Xiang\",\"doi\":\"10.1109/ICAWST.2011.6163135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alga microscopic image usually has a lot of noises and blurs. So a proper image enhancement algorithm which can remove noise and retain detail information is very important for alga microscopic image disposal. In the paper a new image enhancement method based on fuzzy set and subdivision is proposed. It is effective for alga microscopic image disposal. Subdivision scheme's good similarity among different subdivision layers makes the multi-resolution analysis has better approximation between the decomposed signals and the initial image. Subdivision method has strong ability to suppress noise through decomposing the initial image into low pass part. The image can be reconstructed through subdividing the low pass part of the initial image. Then the fuzzy set method is used for enhancement the reconstructed image. A special function is used as membership function in the process of fuzzification. The experimental results demonstrate the effectiveness of the proposed method for alga microscope image diaposal.\",\"PeriodicalId\":126169,\"journal\":{\"name\":\"2011 3rd International Conference on Awareness Science and Technology (iCAST)\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 3rd International Conference on Awareness Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAWST.2011.6163135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2011.6163135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image enhancement method based on fuzzy set and subdivision
Alga microscopic image usually has a lot of noises and blurs. So a proper image enhancement algorithm which can remove noise and retain detail information is very important for alga microscopic image disposal. In the paper a new image enhancement method based on fuzzy set and subdivision is proposed. It is effective for alga microscopic image disposal. Subdivision scheme's good similarity among different subdivision layers makes the multi-resolution analysis has better approximation between the decomposed signals and the initial image. Subdivision method has strong ability to suppress noise through decomposing the initial image into low pass part. The image can be reconstructed through subdividing the low pass part of the initial image. Then the fuzzy set method is used for enhancement the reconstructed image. A special function is used as membership function in the process of fuzzification. The experimental results demonstrate the effectiveness of the proposed method for alga microscope image diaposal.