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A perceptual framework for contrast processing of high dynamic range images

Published: 26 August 2005 Publication History

Abstract

In this work we propose a framework for image processing in a visual response space, in which contrast values directly correlate with their visibility in an image. Our framework involves a transformation of an image from luminance space to a pyramid of low-pass contrast images and then to the visual response space. After modifying response values, the transformation can be reversed to produce the resulting image. To predict the visibility of suprathreshold contrast, we derive a transducer function for the full range of contrast levels that can be found in High Dynamic Range images. We show that a complex contrast compression operation, which preserves textures of small contrast, is reduced to a linear scaling in the proposed visual response space.

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  1. A perceptual framework for contrast processing of high dynamic range images

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        cover image ACM Conferences
        APGV '05: Proceedings of the 2nd symposium on Applied perception in graphics and visualization
        August 2005
        187 pages
        ISBN:1595931392
        DOI:10.1145/1080402
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        Published: 26 August 2005

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        Author Tags

        1. contrast processing
        2. high dynamic range
        3. tone mapping
        4. visual perception

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        View all
        • (2022)Analyzing Perceptual Picture Quality of Various Tone-Mapping Methods for Mobile Devices2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA56318.2022.9904391(1-6)Online publication date: 18-Jul-2022
        • (2022)Haar Wavelet-Based Fusion of Multiple Exposure Images for High Dynamic Range ImagingSN Computer Science10.1007/s42979-021-01010-y3:2Online publication date: 12-Jan-2022
        • (2017)Stereo Vision-Based High Dynamic Range Imaging Using Differently-Exposed Image PairSensors10.3390/s1707147317:7(1473)Online publication date: 22-Jun-2017
        • (2017)A comparative review of tone-mapping algorithms for high dynamic range videoComputer Graphics Forum10.1111/cgf.1314836:2(565-592)Online publication date: 1-May-2017
        • (2016)Perceptual Comparison of Multi-exposure High Dynamic Range and Single-Shot Camera RAW PhotographsImage Analysis and Recognition10.1007/978-3-319-41501-7_18(154-162)Online publication date: 1-Jul-2016
        • (2014)Tone mapping based HDR compressionImage Communication10.1016/j.image.2013.09.00529:2(257-273)Online publication date: 1-Feb-2014
        • (2014)High dynamic range video reconstruction from a stereo camera setupImage Communication10.1016/j.image.2013.08.01629:2(191-202)Online publication date: 1-Feb-2014
        • (2013)Objective Quality Assessment of Tone-Mapped ImagesIEEE Transactions on Image Processing10.1109/TIP.2012.222172522:2(657-667)Online publication date: 1-Feb-2013
        • (2013)Local Edge-Preserving Multiscale Decomposition for High Dynamic Range Image Tone MappingIEEE Transactions on Image Processing10.1109/TIP.2012.221404722:1(70-79)Online publication date: 1-Jan-2013
        • (2011)Perception in graphics, visualization, virtual environments and animationSIGGRAPH Asia 2011 Courses10.1145/2077434.2077448(1-137)Online publication date: 12-Dec-2011
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