Paper Info
Title
An HEVC-Compliant Perceptual Video Coding Scheme based on JND Models for Variable Block-sized Transform Kernels
Abstract
In this paper, an HEVC (High Efficiency Video Coding)-compliant perceptual video coding (PVC) scheme is introduced based on just noticeable difference (JND) models in both transform and pixel domains. We adopt an existing pixel-domain JND model for the transform skip mode (TSM) of HEVC and propose a transform-domain JND model for the transform non-skip modes (non-TSMs) of HEVC. The proposed transform-domain JND model is designed by considering the spatial JND characteristics of contrast sensitivity, luminance adaptation and contrast masking effects as well as by taking into account the summation effects of variable block-sized transforms in HEVC. A temporal JND model is additionally incorporated into the proposed transform-domain JND model to further reduce perceptual redundancy. To incorporate the transform- and pixel-domain JND models into the encoding process in an HEVC-compliant manner, the transform coefficients and residues are suppressed in harmonization with the transform/quantization process and the quantization-only process of HEVC, respectively. To make the JND-based suppression effective, a distortion compensation factor is also proposed to reflect the perceptual distortion in the rate-distortion optimization (RDO) based encoding process. Based on subjective quality assessments of the encoded bitstreams of test sequences, the proposed HEVC- compliant PVC scheme yields remarkable bitrate reductions of a maximum 49.10% and average 16.10% with negligible subjective quality loss, compared to an HEVC reference software (HM 11.0). Also, the proposed HEVC-compliant PVC scheme only increases the encoding complexity of HM 11.0 an average 11.25%.
Year
DOI
Venue
2015
10.1109/TCSVT.2015.2389491
Circuits and Systems for Video Technology, IEEE Transactions  
Keywords
Field
DocType
high efficiency video coding,just noticeable difference,perceptual video coding,encoding,decoding,materials
Computer vision,Pattern recognition,Computer science,Perceptual Distortion,Coding (social sciences),Redundancy (engineering),Artificial intelligence,Pixel,Decoding methods,Quantization (signal processing),Distortion,Encoding (memory)
Journal
Volume
Issue
ISSN
PP
99
1051-8215
Citations 
PageRank 
References 
19
0.80
24
Authors
3
Name
Order
Citations
PageRank
Jaeil Kim1635.46
Sung-Ho Bae218110.54
Munchurl Kim385868.28