Visual masking estimation based on structural uncertainty
A model of visual masking, which reveals the visible threshold of human perception, is useful in perceptual based image/video processing. The existing visual masking formulation, which mainly considers luminance contrast, cannot accurately estimate the visible threshold. Recent researches indicate t...
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sg-ntu-dr.10356-843142020-05-28T07:41:41Z Visual masking estimation based on structural uncertainty Lin, Weisi Wu, Jinjian. Shi, Guangming. School of Computer Engineering IEEE International Symposium on Circuits and Systems (2013 : Beijing, China) A model of visual masking, which reveals the visible threshold of human perception, is useful in perceptual based image/video processing. The existing visual masking formulation, which mainly considers luminance contrast, cannot accurately estimate the visible threshold. Recent researches indicate that human perception is highly adaptive to extract orderly structures and is insensitive to disorderly structures. Therefore, we suggest that the structural characteristic is another determining factor for visual masking, and deduce a novel visual masking function based on structural uncertainty. Experimental results demonstrate that the proposed model is more consistent with human perception than the existing visual masking model. 2013-10-25T08:51:26Z 2019-12-06T15:42:35Z 2013-10-25T08:51:26Z 2019-12-06T15:42:35Z 2013 2013 Conference Paper Wu, J., Lin, W., & Shi, G. (2013). Visual masking estimation based on structural uncertainty. 2013 IEEE International Symposium on Circuits and Systems (ISCAS), 933-936. https://hdl.handle.net/10356/84314 http://hdl.handle.net/10220/16937 10.1109/ISCAS.2013.6572001 en |
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A model of visual masking, which reveals the visible threshold of human perception, is useful in perceptual based image/video processing. The existing visual masking formulation, which mainly considers luminance contrast, cannot accurately estimate the visible threshold. Recent researches indicate that human perception is highly adaptive to extract orderly structures and is insensitive to disorderly structures. Therefore, we suggest that the structural characteristic is another determining factor for visual masking, and deduce a novel visual masking function based on structural uncertainty. Experimental results demonstrate that the proposed model is more consistent with human perception than the existing visual masking model. |
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School of Computer Engineering |
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School of Computer Engineering Lin, Weisi Wu, Jinjian. Shi, Guangming. |
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Conference or Workshop Item |
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Lin, Weisi Wu, Jinjian. Shi, Guangming. |
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Lin, Weisi Wu, Jinjian. Shi, Guangming. Visual masking estimation based on structural uncertainty |
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Lin, Weisi |
title |
Visual masking estimation based on structural uncertainty |
title_short |
Visual masking estimation based on structural uncertainty |
title_full |
Visual masking estimation based on structural uncertainty |
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Visual masking estimation based on structural uncertainty |
title_full_unstemmed |
Visual masking estimation based on structural uncertainty |
title_sort |
visual masking estimation based on structural uncertainty |
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2013 |
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https://hdl.handle.net/10356/84314 http://hdl.handle.net/10220/16937 |
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