Visual attention guided pixel-wise just noticeable difference model

The just noticeable difference (JND) models in pixel domain are generally composed of luminance adaptation (LA) and contrast masking (CM), which takes edge masking (EM) and texture masking (TM) into consideration. However, in existing pixel-wise JND models, CM is not evaluated appropriately since th...

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Main Authors: Zeng, Zhipeng, Zeng, Huanqiang, Chen, Jing, Zhu, Jianqing, Zhang, Yun, Ma, Kai-Kuang
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/146581
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1465812021-03-02T02:57:28Z Visual attention guided pixel-wise just noticeable difference model Zeng, Zhipeng Zeng, Huanqiang Chen, Jing Zhu, Jianqing Zhang, Yun Ma, Kai-Kuang School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Just Noticeable Difference Orientation Complexity The just noticeable difference (JND) models in pixel domain are generally composed of luminance adaptation (LA) and contrast masking (CM), which takes edge masking (EM) and texture masking (TM) into consideration. However, in existing pixel-wise JND models, CM is not evaluated appropriately since they overestimate the masking effect of regular oriented texture regions and neglect the visual attention characteristic of human eyes for the real image. In this work, a novel JND model in pixel domain is proposed, where orderly texture masking (OTM) for regular texture areas (also called orderly texture regions) and disorderly texture masking (DTM) for complex texture areas (also called disorderly texture regions) are presented based on the orientation complexity. Meanwhile, the visual saliency is set as the weighting factor and is incorporated into CM evaluation to enhance JND thresholds. Experimental results indicate that compared with existing relevant JND profiles, the proposed JND model tolerates more distortion in the same perceptual quality, and brings better visual perception in the same level of the injected JND-noise energy. Published version 2021-03-02T02:57:28Z 2021-03-02T02:57:28Z 2019 Journal Article Zeng, Z., Zeng, H., Chen, J., Zhu, J., Zhang, Y., & Ma, K.-K. (2019). Visual attention guided pixel-wise just noticeable difference model. IEEE Access, 7, 132111-132119. doi:10.1109/access.2019.2939569 2169-3536 0000-0002-2802-7745 0000-0001-9457-7801 https://hdl.handle.net/10356/146581 10.1109/ACCESS.2019.2939569 2-s2.0-85077958721 7 132111 132119 en IEEE Access © 2019 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Just Noticeable Difference
Orientation Complexity
spellingShingle Engineering::Electrical and electronic engineering
Just Noticeable Difference
Orientation Complexity
Zeng, Zhipeng
Zeng, Huanqiang
Chen, Jing
Zhu, Jianqing
Zhang, Yun
Ma, Kai-Kuang
Visual attention guided pixel-wise just noticeable difference model
description The just noticeable difference (JND) models in pixel domain are generally composed of luminance adaptation (LA) and contrast masking (CM), which takes edge masking (EM) and texture masking (TM) into consideration. However, in existing pixel-wise JND models, CM is not evaluated appropriately since they overestimate the masking effect of regular oriented texture regions and neglect the visual attention characteristic of human eyes for the real image. In this work, a novel JND model in pixel domain is proposed, where orderly texture masking (OTM) for regular texture areas (also called orderly texture regions) and disorderly texture masking (DTM) for complex texture areas (also called disorderly texture regions) are presented based on the orientation complexity. Meanwhile, the visual saliency is set as the weighting factor and is incorporated into CM evaluation to enhance JND thresholds. Experimental results indicate that compared with existing relevant JND profiles, the proposed JND model tolerates more distortion in the same perceptual quality, and brings better visual perception in the same level of the injected JND-noise energy.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zeng, Zhipeng
Zeng, Huanqiang
Chen, Jing
Zhu, Jianqing
Zhang, Yun
Ma, Kai-Kuang
format Article
author Zeng, Zhipeng
Zeng, Huanqiang
Chen, Jing
Zhu, Jianqing
Zhang, Yun
Ma, Kai-Kuang
author_sort Zeng, Zhipeng
title Visual attention guided pixel-wise just noticeable difference model
title_short Visual attention guided pixel-wise just noticeable difference model
title_full Visual attention guided pixel-wise just noticeable difference model
title_fullStr Visual attention guided pixel-wise just noticeable difference model
title_full_unstemmed Visual attention guided pixel-wise just noticeable difference model
title_sort visual attention guided pixel-wise just noticeable difference model
publishDate 2021
url https://hdl.handle.net/10356/146581
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