{"title":"Smart tone reproduction","authors":"Dun-Yu Hsiao, H. Liao","doi":"10.1109/ICASSP.2008.4517851","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an effective scheme to enhance the visual details at the minimal cost of user adjustments. The uprising importance of automatic tone reproduction comes from the increasing population of digital archive programs, which contains a large number of images/videos either old irreproducible, or poorly captured. We attempt to solve above issues by a new local normalization step and an adaptive contrast assessment process. With those two processes, our method can effectively enhance poor quality regions and simultaneously preserving good quality ones with default parameter settings. The experimental results demonstrate that our method is superior to many existing algorithms when applied to aid digital archiving issues.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2008.4517851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we propose an effective scheme to enhance the visual details at the minimal cost of user adjustments. The uprising importance of automatic tone reproduction comes from the increasing population of digital archive programs, which contains a large number of images/videos either old irreproducible, or poorly captured. We attempt to solve above issues by a new local normalization step and an adaptive contrast assessment process. With those two processes, our method can effectively enhance poor quality regions and simultaneously preserving good quality ones with default parameter settings. The experimental results demonstrate that our method is superior to many existing algorithms when applied to aid digital archiving issues.
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智能音色再现
在本文中,我们提出了一种有效的方案来增强视觉细节,以最小的用户调整成本。自动音色再现的重要性来自于数字档案程序的不断增加,其中包含大量的图像/视频,要么是旧的不可复制的,要么是捕捉不好的。我们尝试通过新的局部归一化步骤和自适应对比评估过程来解决上述问题。通过这两个过程,我们的方法可以有效地增强质量较差的区域,同时保留默认参数设置的质量较好的区域。实验结果表明,该方法在辅助数字存档问题上优于现有的许多算法。
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