{"title":"使用基于子图像直方图均衡化的引导滤波器保持色相的彩色图像增强","authors":"Nitish Vig, S. Budhiraja, Jaget Singh","doi":"10.1109/IC3.2016.7880244","DOIUrl":null,"url":null,"abstract":"The images, captured by camera, might suffer from poor contrast, saturation artefacts or improper brightness. Hence, image enhancement becomes an important step to improve the quality of image. Images are enhanced such that there is change in intensity or saturation component, keeping hue unchanged. Often, gamut problem arises when transforming from one plane to another. In this paper, the technique focusses on enhancing the contrast of low illumination images while at the same time maintaining the brightness. A function called exposure, is used in estimation of underexposed and highly underexposed images. The brightness of the input image is increased using transformation functions, which is then treated as target image so that the brightness of input image is adjusted close to target image, using histogram matching. The existing technique Exposure based Sub Image Histogram Equalization (ESIHE), is used to increase the visual quality, which is followed by guided image filter for edge smoothening. Simulation shows that this proposed technique has better contrast enhancement, brightness preservation, hue preservation and better entropy, without gamut problem.","PeriodicalId":294210,"journal":{"name":"2016 Ninth International Conference on Contemporary Computing (IC3)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Hue preserving color image enhancement using guided filter based sub image histogram equalization\",\"authors\":\"Nitish Vig, S. Budhiraja, Jaget Singh\",\"doi\":\"10.1109/IC3.2016.7880244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The images, captured by camera, might suffer from poor contrast, saturation artefacts or improper brightness. Hence, image enhancement becomes an important step to improve the quality of image. Images are enhanced such that there is change in intensity or saturation component, keeping hue unchanged. Often, gamut problem arises when transforming from one plane to another. In this paper, the technique focusses on enhancing the contrast of low illumination images while at the same time maintaining the brightness. A function called exposure, is used in estimation of underexposed and highly underexposed images. The brightness of the input image is increased using transformation functions, which is then treated as target image so that the brightness of input image is adjusted close to target image, using histogram matching. The existing technique Exposure based Sub Image Histogram Equalization (ESIHE), is used to increase the visual quality, which is followed by guided image filter for edge smoothening. Simulation shows that this proposed technique has better contrast enhancement, brightness preservation, hue preservation and better entropy, without gamut problem.\",\"PeriodicalId\":294210,\"journal\":{\"name\":\"2016 Ninth International Conference on Contemporary Computing (IC3)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Ninth International Conference on Contemporary Computing (IC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3.2016.7880244\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Ninth International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2016.7880244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hue preserving color image enhancement using guided filter based sub image histogram equalization
The images, captured by camera, might suffer from poor contrast, saturation artefacts or improper brightness. Hence, image enhancement becomes an important step to improve the quality of image. Images are enhanced such that there is change in intensity or saturation component, keeping hue unchanged. Often, gamut problem arises when transforming from one plane to another. In this paper, the technique focusses on enhancing the contrast of low illumination images while at the same time maintaining the brightness. A function called exposure, is used in estimation of underexposed and highly underexposed images. The brightness of the input image is increased using transformation functions, which is then treated as target image so that the brightness of input image is adjusted close to target image, using histogram matching. The existing technique Exposure based Sub Image Histogram Equalization (ESIHE), is used to increase the visual quality, which is followed by guided image filter for edge smoothening. Simulation shows that this proposed technique has better contrast enhancement, brightness preservation, hue preservation and better entropy, without gamut problem.