{"title":"利用模糊集理论增强低对比度图像","authors":"K. Hasikin, N. Isa","doi":"10.1109/UKSim.2012.60","DOIUrl":null,"url":null,"abstract":"This paper presents a fuzzy grayscale enhancement technique for low contrast image. The degradation of the low contrast image is mainly caused by the inadequate lighting during image capturing and thus eventually resulted in nonuniform illumination in the image. Most of the developed contrast enhancement techniques improved image quality without considering the nonuniform lighting in the image. The fuzzy grayscale image enhancement technique is proposed by maximizing fuzzy measures contained in the image. The membership function is then modified to enhance the image by using power-law transformation and saturation operator. The qualitative and quantitative performances of the proposed method are compared with the other methods. The proposed method produced better quality enhanced image and required minimum processing time than the other methods.","PeriodicalId":405479,"journal":{"name":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"97","resultStr":"{\"title\":\"Enhancement of the Low Contrast Image Using Fuzzy Set Theory\",\"authors\":\"K. Hasikin, N. Isa\",\"doi\":\"10.1109/UKSim.2012.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a fuzzy grayscale enhancement technique for low contrast image. The degradation of the low contrast image is mainly caused by the inadequate lighting during image capturing and thus eventually resulted in nonuniform illumination in the image. Most of the developed contrast enhancement techniques improved image quality without considering the nonuniform lighting in the image. The fuzzy grayscale image enhancement technique is proposed by maximizing fuzzy measures contained in the image. The membership function is then modified to enhance the image by using power-law transformation and saturation operator. The qualitative and quantitative performances of the proposed method are compared with the other methods. The proposed method produced better quality enhanced image and required minimum processing time than the other methods.\",\"PeriodicalId\":405479,\"journal\":{\"name\":\"2012 UKSim 14th International Conference on Computer Modelling and Simulation\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"97\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 UKSim 14th International Conference on Computer Modelling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UKSim.2012.60\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 UKSim 14th International Conference on Computer Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UKSim.2012.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancement of the Low Contrast Image Using Fuzzy Set Theory
This paper presents a fuzzy grayscale enhancement technique for low contrast image. The degradation of the low contrast image is mainly caused by the inadequate lighting during image capturing and thus eventually resulted in nonuniform illumination in the image. Most of the developed contrast enhancement techniques improved image quality without considering the nonuniform lighting in the image. The fuzzy grayscale image enhancement technique is proposed by maximizing fuzzy measures contained in the image. The membership function is then modified to enhance the image by using power-law transformation and saturation operator. The qualitative and quantitative performances of the proposed method are compared with the other methods. The proposed method produced better quality enhanced image and required minimum processing time than the other methods.