{"title":"减少HDR图像的范围以向后兼容LDR图像处理","authors":"M. Iwahashi, Taichi Yoshida, H. Kiya","doi":"10.1109/APSIPA.2014.7041617","DOIUrl":null,"url":null,"abstract":"This paper proposes a new range reduction method with the minimum amount of quantization error in the L2 norm under the L infinity norm constraint. It is necessary to reduce dynamic range of pixel values of high dynamic range (HDR) images to have backward compatibility with low dynamic range image processing systems. The simplest approach is to truncate lower bit planes in binary representation of pixel values. However it does not have fine granularity of the reduced range, and also it does not utilize the histogram sparseness. Furthermore, it generates significant amount of quantization errors. In this paper, we propose a new range reduction method which can 1) utilize the histogram sparseness, and also 2) minimize variance of the error 3) under a specified maximum absolute value of the error.","PeriodicalId":231382,"journal":{"name":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Range reduction of HDR images for backward compatibility with LDR image processing\",\"authors\":\"M. Iwahashi, Taichi Yoshida, H. Kiya\",\"doi\":\"10.1109/APSIPA.2014.7041617\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new range reduction method with the minimum amount of quantization error in the L2 norm under the L infinity norm constraint. It is necessary to reduce dynamic range of pixel values of high dynamic range (HDR) images to have backward compatibility with low dynamic range image processing systems. The simplest approach is to truncate lower bit planes in binary representation of pixel values. However it does not have fine granularity of the reduced range, and also it does not utilize the histogram sparseness. Furthermore, it generates significant amount of quantization errors. In this paper, we propose a new range reduction method which can 1) utilize the histogram sparseness, and also 2) minimize variance of the error 3) under a specified maximum absolute value of the error.\",\"PeriodicalId\":231382,\"journal\":{\"name\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2014.7041617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2014.7041617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Range reduction of HDR images for backward compatibility with LDR image processing
This paper proposes a new range reduction method with the minimum amount of quantization error in the L2 norm under the L infinity norm constraint. It is necessary to reduce dynamic range of pixel values of high dynamic range (HDR) images to have backward compatibility with low dynamic range image processing systems. The simplest approach is to truncate lower bit planes in binary representation of pixel values. However it does not have fine granularity of the reduced range, and also it does not utilize the histogram sparseness. Furthermore, it generates significant amount of quantization errors. In this paper, we propose a new range reduction method which can 1) utilize the histogram sparseness, and also 2) minimize variance of the error 3) under a specified maximum absolute value of the error.