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Download fileA novel information hiding method for H.266/VVC based on selections of luminance transform and chrominance prediction modes
conference contribution
posted on 2021-10-07, 11:33 authored by Xiyao Liu, Kaiyue Shi, Aihua Li, Hao Zhang, Jiang Ming, Hui FangHui FangThis paper proposes a novel information hiding
method designed for H.266/Versatile Video Coding (VVC)
compressed video streams. In this work, we explore two exclusive tools in H.266/VVC standard, named Multiple Transform
Selection (MTS) and Cross-component linear model (CCLM),
to embed information. These two tools are utilized to preserve
high video reconstruction quality and compression efficiency
as well as enhance embedding capacity. In specific, MTS is for
embedding information into luminance blocks by modifying
the selections of coding transforms. Comparing with other
tools, MTS has less significant impact on compression quality
and efficiency. In addition, CCLM is further used to embed
information into chrominance blocks to further enlarge the
embedding capacity with little impact on the other two metrics.
To our best knowledge, it is the first information hiding method
exclusively designed for H.266/VVC. Experimental results show
that our proposed information hiding method ensures high embedding capacity, remarkable video reconstruction quality and
insignificant impact on compression efficiency, which achieves
a better overall performances comparing to existing methods
for compressed video.
Funding
National Natural Science Foundation of China (61602527)
Natural Science Foundation of Hunan Province, China (2020JJ4746, 2017JJ3416)
History
School
- Science
Department
- Computer Science
Published in
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)Pages
3158 - 3163Source
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2021-07-24Publication date
2022-01-06Copyright date
2021ISBN
9781665442077eISSN
2577-1655Publisher version
Language
- en