Paper Info
Title
Advanced H.264/AVC-Based Perceptual Video Coding: Architecture, Tools, and Assessment
Abstract
The characteristics of the human visual system may be further exploited in lossy video coding to improve the video compression efficiency beyond the state-of-the-art H.264/AVC standard. Although the literature is rich in solutions to model the human visual system characteristics, the performance and real benefits brought by these models have not been fully integrated and assessed yet. Moreover, the rate-distortion (RD) performance is usually measured by means of methodologies that do not account for the implicit variability of the observers when rating the video quality. In this context, the novelty brought by this paper is threefold: first, it proposes novel perceptual video coding tools, notably decoder side just noticeable distortion (JND) model estimation to perceptually allocate the available rate with the finest level of granularity while avoiding the extra rate associated to coding the varying quantization steps. Second, it proposes an integrated, powerful H.264/AVC-based perceptual video coding architecture embedding a state-of-the-art JND model based on spatio-temporal human visual system masking mechanisms; this model is exploited for both the aforementioned rate allocation as well as to perceptually weight the distortion used in the motion estimation and RD optimization. Finally, it proposes a relative assessment methodology to measure the RD performance of a perceptual video codec (PVC) with respect to another codec taken as reference. The methodology considers the implicit observers variability when rating video quality which leads to a nonlinear sensitivity of the objective metrics used for quality assessment. The obtained RD performance, measured according to this methodology, shows an average bitrate reduction of up to 30% when the proposed PVC is compared with the H.264/AVC High profile at the same objective quality level. Moreover, the proposed perceptual codec outperforms an alternative perceptual codec recently published in the literature.
Year
DOI
Venue
2011
10.1109/TCSVT.2011.2130430
Circuits and Systems for Video Technology, IEEE Transactions
Keywords
Field
DocType
motion estimation,video codecs,video coding,H.264-AVC based perceptual video coding,just noticeable distortion model,motion estimation,nonlinear sensitivity,perceptual video codec,quality assessment,rate allocation,rate-distortion performance,spatiotemporal human visual system masking mechanisms,varying quantization steps,video quality,Objective quality metric resolving power,perceptual video coding,spatio-temporal JND model
Computer vision,Average bitrate,Human visual system model,Computer science,Speech recognition,Subjective video quality,Artificial intelligence,Data compression,Video quality,Codec,Scalable Video Coding,Context-adaptive binary arithmetic coding
Journal
Volume
Issue
ISSN
21
6
1051-8215
Citations 
PageRank 
References 
30
1.08
24
Authors
2
Name
Order
Citations
PageRank
Naccari, M.1301.08
Fernando Pereira2177172124.79