{"title":"基于标准差和模式的图像增强双直方图均衡化算法","authors":"Kuldip Acharya, D. Ghoshal","doi":"10.2139/ssrn.3768018","DOIUrl":null,"url":null,"abstract":"This paper presents an enhancement method for image enhancement in poor lighting condition. Standard deviation and mode are computed on the image histogram. Histogram clipping process is done to limit the rate of over enhancement by mode-based threshold value. The clipped histogram is divided into two segments founded on a threshold value computed by the standard deviation on the image histogram. Two sub-images of the individual histogram are equalized and combined to form the output image that preserves the entropy and produced better contrast enhancement image. The results in terms of Universal Image Quality Index (UIQI), and Entropy, for images, have been simulated on MATLAB. The outcomes produced by the proposed method have been ompared with the results gotten from existing image enhancement methods. It has been observed from the outcomes that proposed method outperform previous methods.","PeriodicalId":363330,"journal":{"name":"Computation Theory eJournal","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Standard Deviation and Mode Based Bi-Histogram Equalization Algorithm for Image Enhancement\",\"authors\":\"Kuldip Acharya, D. Ghoshal\",\"doi\":\"10.2139/ssrn.3768018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an enhancement method for image enhancement in poor lighting condition. Standard deviation and mode are computed on the image histogram. Histogram clipping process is done to limit the rate of over enhancement by mode-based threshold value. The clipped histogram is divided into two segments founded on a threshold value computed by the standard deviation on the image histogram. Two sub-images of the individual histogram are equalized and combined to form the output image that preserves the entropy and produced better contrast enhancement image. The results in terms of Universal Image Quality Index (UIQI), and Entropy, for images, have been simulated on MATLAB. The outcomes produced by the proposed method have been ompared with the results gotten from existing image enhancement methods. It has been observed from the outcomes that proposed method outperform previous methods.\",\"PeriodicalId\":363330,\"journal\":{\"name\":\"Computation Theory eJournal\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computation Theory eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3768018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computation Theory eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3768018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Standard Deviation and Mode Based Bi-Histogram Equalization Algorithm for Image Enhancement
This paper presents an enhancement method for image enhancement in poor lighting condition. Standard deviation and mode are computed on the image histogram. Histogram clipping process is done to limit the rate of over enhancement by mode-based threshold value. The clipped histogram is divided into two segments founded on a threshold value computed by the standard deviation on the image histogram. Two sub-images of the individual histogram are equalized and combined to form the output image that preserves the entropy and produced better contrast enhancement image. The results in terms of Universal Image Quality Index (UIQI), and Entropy, for images, have been simulated on MATLAB. The outcomes produced by the proposed method have been ompared with the results gotten from existing image enhancement methods. It has been observed from the outcomes that proposed method outperform previous methods.