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Visually lossless coding in HEVC : a high bit depth and 4:4:4 capable JND-based perceptual quantisation technique for HEVC
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Prangnell, Lee (2018) Visually lossless coding in HEVC : a high bit depth and 4:4:4 capable JND-based perceptual quantisation technique for HEVC. Signal Processing: Image Communication, 63 . pp. 125-140. doi:10.1016/j.image.2018.02.007
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WRAP-visually-lossless-coding-HEVC-Prangnell-2018.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (8Mb) | Preview |
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WRAP-visually-lossless-coding-HEVC-quantisation-Prangnell-2017.pdf - Submitted Version - Requires a PDF viewer. Download (7Mb) | Preview |
Official URL: https://doi.org/10.1016/j.image.2018.02.007
Abstract
Due to the increasing prevalence of high bit depth and YCbCr 4:4:4 video data, it is desirable to develop a JND-based visually lossless coding technique which can account for high bit depth 4:4:4 data in addition to standard 8-bit precision chroma subsampled data. In this paper, we propose a Coding Block (CB)-level JND-based luma and chroma perceptual quantisation technique for HEVC named Pixel-PAQ. Pixel-PAQ exploits both luminance masking and chrominance masking to achieve JND-based visually lossless coding; the proposed method is compatible with high bit depth YCbCr 4:4:4 video data of any resolution. When applied to YCbCr 4:4:4 high bit depth video data, Pixel-PAQ can achieve vast bitrate reductions – of up to 75% (68.6% over four QP data points) – compared with a state-of-the-art luma-based JND method for HEVC named IDSQ. Moreover, the participants in the subjective evaluations confirm that visually lossless coding is successfully achieved by Pixel-PAQ (at a PSNR value of 28.04 dB in one test).
| Item Type: | Journal Article | ||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science > Computer Science | ||||||||||
| Library of Congress Subject Headings (LCSH): | Digital video -- Standards, Video compression | ||||||||||
| Journal or Publication Title: | Signal Processing: Image Communication | ||||||||||
| Publisher: | Elsevier Science Inc | ||||||||||
| ISSN: | 0923-5965 | ||||||||||
| Official Date: | April 2018 | ||||||||||
| Dates: |
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| Date of first compliant deposit: | 20 February 2018 | ||||||||||
| Volume: | 63 | ||||||||||
| Page Range: | pp. 125-140 | ||||||||||
| DOI: | 10.1016/j.image.2018.02.007 | ||||||||||
| Status: | Peer Reviewed | ||||||||||
| Publication Status: | Published | ||||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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