Wilawun Punmanee, T. Kasetkasem, T. Chanwimaluang, A. Nishihara
{"title":"THEOS图像的自然色彩增强","authors":"Wilawun Punmanee, T. Kasetkasem, T. Chanwimaluang, A. Nishihara","doi":"10.1109/ISCIT.2013.6645914","DOIUrl":null,"url":null,"abstract":"Color naturalness is crucial for visual interpretation and display of satellite images. Since optical sensors in some satellite such as THEOS do not cover the whole wavelength range of red, green and blue color spectrums, the captured images may appear to have unnatural colors. It is imperative to correct the unnatural colors in these images. To achieve this goal, we must first measure the color naturalness of satellite images. As a result, we propose a novel metric for measuring color naturalness through the satellite image color naturalness index (SICNI). Here, the SICNI is desired to measure color naturalness of satellite images based on the perception of the human visual system. We compare the SICNI with evaluation from satellite image experts, and achieve the correlation score of 0.897. Based on the proposed SICNI, we develop the color enhancement algorithm for satellite images by transformation of color vectors in the CIELUV color space such that the SICNI is maximized.","PeriodicalId":356009,"journal":{"name":"2013 13th International Symposium on Communications and Information Technologies (ISCIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Naturalness color enhancement for THEOS images\",\"authors\":\"Wilawun Punmanee, T. Kasetkasem, T. Chanwimaluang, A. Nishihara\",\"doi\":\"10.1109/ISCIT.2013.6645914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Color naturalness is crucial for visual interpretation and display of satellite images. Since optical sensors in some satellite such as THEOS do not cover the whole wavelength range of red, green and blue color spectrums, the captured images may appear to have unnatural colors. It is imperative to correct the unnatural colors in these images. To achieve this goal, we must first measure the color naturalness of satellite images. As a result, we propose a novel metric for measuring color naturalness through the satellite image color naturalness index (SICNI). Here, the SICNI is desired to measure color naturalness of satellite images based on the perception of the human visual system. We compare the SICNI with evaluation from satellite image experts, and achieve the correlation score of 0.897. Based on the proposed SICNI, we develop the color enhancement algorithm for satellite images by transformation of color vectors in the CIELUV color space such that the SICNI is maximized.\",\"PeriodicalId\":356009,\"journal\":{\"name\":\"2013 13th International Symposium on Communications and Information Technologies (ISCIT)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 13th International Symposium on Communications and Information Technologies (ISCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCIT.2013.6645914\",\"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 13th International Symposium on Communications and Information Technologies (ISCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCIT.2013.6645914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Color naturalness is crucial for visual interpretation and display of satellite images. Since optical sensors in some satellite such as THEOS do not cover the whole wavelength range of red, green and blue color spectrums, the captured images may appear to have unnatural colors. It is imperative to correct the unnatural colors in these images. To achieve this goal, we must first measure the color naturalness of satellite images. As a result, we propose a novel metric for measuring color naturalness through the satellite image color naturalness index (SICNI). Here, the SICNI is desired to measure color naturalness of satellite images based on the perception of the human visual system. We compare the SICNI with evaluation from satellite image experts, and achieve the correlation score of 0.897. Based on the proposed SICNI, we develop the color enhancement algorithm for satellite images by transformation of color vectors in the CIELUV color space such that the SICNI is maximized.