Prangnell, Lee, Hernández-Cabronero, Miguel and Sanchez Silva, Victor (2018) Coding block-level perceptual video coding for 4:4:4 data in HEVC. In: IEEE International Conference on Image Processing (ICIP 2017), Beijing, China, 17-20 Sep 2017. Published in: 2017 IEEE International Conference on Image Processing (ICIP) doi:10.1109/ICIP.2017.8296730 ISSN 2381-8549.

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Abstract

There is an increasing consumer demand for high bit-depth 4:4:4 HD video data playback due to its superior perceptual visual quality compared with standard 8-bit subsampled 4:2:0 video data. Due to vast file sizes and associated bitrates, it is desirable to compress raw high bit-depth 4:4:4 HD video sequences as much as possible without incurring a discernible decrease in visual quality. In this paper, we propose a Coding Block (CB)-level perceptual video coding technique for HEVC named Full Color Perceptual Quantization (FCPQ). FCPQ is designed to adjust the Quantization Parameter (QP) at the CB level - i.e., the luma CB and the chroma Cb and Cr CBs - according to the variances of pixel data in each CB. FCPQ is based on the default perceptual quantization method in HEVC called AdaptiveQP. AdaptiveQP adjusts the QP of an entire 2N×2N CU based only on the spatial activity of the constituent luma CB. As demonstrated in this paper, by not accounting for the spatial activity of the constituent chroma CBs, as is the case with AdaptiveQP, coding performance can be significantly affected; this is because the variance of pixel data in a luma CB is notably different from the variances of pixel data in chroma Cb and Cr CBs. FCPQ, therefore, addresses this problem. In terms of coding performance, FCPQ achieves BD-Rate improvements of up to 39.5% (Y), 16% (Cb) and 29.9% (Cr) compared with AdaptiveQP.

Item Type:	Conference Item (Paper)
Subjects:	T Technology > TR Photography
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH):	High definition video recording , Video compression
Journal or Publication Title:	2017 IEEE International Conference on Image Processing (ICIP)
Publisher:	IEEE
ISSN:	2381-8549
Official Date:	22 February 2018
Dates:	Date Event 22 February 2018 Published 30 May 2017 Updated 8 May 2017 Accepted
DOI:	10.1109/ICIP.2017.8296730
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	10 May 2017
Date of first compliant Open Access:	10 May 2017
Funder:	Engineering and Physical Sciences Research Council (EPSRC)
Grant number:	P83801G
Conference Paper Type:	Paper
Title of Event:	IEEE International Conference on Image Processing (ICIP 2017)
Type of Event:	Conference
Location of Event:	Beijing, China
Date(s) of Event:	17-20 Sep 2017
Related URLs:	Organisation

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