{"title":"一种用于直方图均衡化的子图像边缘保持方法","authors":"Yan-Tsung Peng, Bing-Chuan Tsai, S. Ruan","doi":"10.1109/ICICS.2013.6782961","DOIUrl":null,"url":null,"abstract":"Histogram equalization (HE) is widely used in image contrast enhancement. It basically equalizes the image histogram to improve the contrast of the input image. In this paper, we propose a Sub-Image Edge Preservation (SIEP) method applied to HE-based contrast enhancement algorithms to further preserve edges in the histogram-equalized images and enhance local contrast. In this method, the input image is partitioned into different sub-images and in turn, the local transform function of each sub-image is generated respectively by applying a HE-based contrast enhancement method. Moreover, it exploits the total of gradients in each sub-image to weigh each local transform function for generating a global transform function to enhance overall image contrast while preserving edges. Experimental results show the efficacy of our method for a better edge preserving rate.","PeriodicalId":184544,"journal":{"name":"2013 9th International Conference on Information, Communications & Signal Processing","volume":"623 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Sub-Image Edge Preservation method for histogram equalization\",\"authors\":\"Yan-Tsung Peng, Bing-Chuan Tsai, S. Ruan\",\"doi\":\"10.1109/ICICS.2013.6782961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Histogram equalization (HE) is widely used in image contrast enhancement. It basically equalizes the image histogram to improve the contrast of the input image. In this paper, we propose a Sub-Image Edge Preservation (SIEP) method applied to HE-based contrast enhancement algorithms to further preserve edges in the histogram-equalized images and enhance local contrast. In this method, the input image is partitioned into different sub-images and in turn, the local transform function of each sub-image is generated respectively by applying a HE-based contrast enhancement method. Moreover, it exploits the total of gradients in each sub-image to weigh each local transform function for generating a global transform function to enhance overall image contrast while preserving edges. Experimental results show the efficacy of our method for a better edge preserving rate.\",\"PeriodicalId\":184544,\"journal\":{\"name\":\"2013 9th International Conference on Information, Communications & Signal Processing\",\"volume\":\"623 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th International Conference on Information, Communications & Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICS.2013.6782961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th International Conference on Information, Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICS.2013.6782961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Sub-Image Edge Preservation method for histogram equalization
Histogram equalization (HE) is widely used in image contrast enhancement. It basically equalizes the image histogram to improve the contrast of the input image. In this paper, we propose a Sub-Image Edge Preservation (SIEP) method applied to HE-based contrast enhancement algorithms to further preserve edges in the histogram-equalized images and enhance local contrast. In this method, the input image is partitioned into different sub-images and in turn, the local transform function of each sub-image is generated respectively by applying a HE-based contrast enhancement method. Moreover, it exploits the total of gradients in each sub-image to weigh each local transform function for generating a global transform function to enhance overall image contrast while preserving edges. Experimental results show the efficacy of our method for a better edge preserving rate.