Signal-independent separable KLT by offline training for video coding

After the works on High Efficiency Video Coding (HEVC) standard, the standard organizations continued to study the next generation of video coding standard, named Versatile Video Coding (VVC). The compression capacity of the VVC standard is expected to be substantially improved relative to the curre...

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Main Authors: Fan, Kui, Wang, Ronggang, Lin, Weisi, Duan, Ling-Yu, Gao, Wen
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2019
Subjects:
KLT
Online Access:https://hdl.handle.net/10356/106296
http://hdl.handle.net/10220/48882
http://dx.doi.org/10.1109/ACCESS.2019.2903734
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1062962019-12-06T22:08:22Z Signal-independent separable KLT by offline training for video coding Fan, Kui Wang, Ronggang Lin, Weisi Duan, Ling-Yu Gao, Wen School of Computer Science and Engineering KLT Transform DRNTU::Engineering::Computer science and engineering After the works on High Efficiency Video Coding (HEVC) standard, the standard organizations continued to study the next generation of video coding standard, named Versatile Video Coding (VVC). The compression capacity of the VVC standard is expected to be substantially improved relative to the current HEVC standard by evolving the potential coding tools greatly. Transform is a key technique for compression efficiency, and core experiment 6 (CE6) in JVET is established to explore the transform-related coding tools. In this paper, we propose a novel signal-independent separable transform based on the Karhunen-Loève transform (KLT) to improve the efficiency of both intra and inter residual coding. In the proposed method, the drawbacks of the traditional KLT are addressed. A group of mode-independent intra transform matrices is calculated from abundant intra residual samples of all intra modes, while the inter separable KLT matrices are trained with the residuals that cannot be efficiently processed by the discrete cosine transform type II (DCT-II). The separable KLT is developed as an additional transform type apart from DCT-II. The experimental results show that the proposed method can achieve 2.7% and 1.5% bitrate saving averagely under All Intra and Random Access configurations on top of the reference software of VVC (VTM-1.1). In addition, the consistent performance improvement on test set also validates the property of signal independency and the strong generalization capacity of the proposed separable KLT. NRF (Natl Research Foundation, S’pore) Published version 2019-06-20T08:25:26Z 2019-12-06T22:08:22Z 2019-06-20T08:25:26Z 2019-12-06T22:08:22Z 2019 Journal Article Fan, K., Wang, R., Lin, W., Duan, L.-Y., & Gao, W. (2019). Signal-independent separable KLT by offline training for video coding. IEEE Access, 7, 33087-33093. doi:10.1109/ACCESS.2019.2903734 https://hdl.handle.net/10356/106296 http://hdl.handle.net/10220/48882 http://dx.doi.org/10.1109/ACCESS.2019.2903734 en IEEE Access © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 7 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic KLT
Transform
DRNTU::Engineering::Computer science and engineering
spellingShingle KLT
Transform
DRNTU::Engineering::Computer science and engineering
Fan, Kui
Wang, Ronggang
Lin, Weisi
Duan, Ling-Yu
Gao, Wen
Signal-independent separable KLT by offline training for video coding
description After the works on High Efficiency Video Coding (HEVC) standard, the standard organizations continued to study the next generation of video coding standard, named Versatile Video Coding (VVC). The compression capacity of the VVC standard is expected to be substantially improved relative to the current HEVC standard by evolving the potential coding tools greatly. Transform is a key technique for compression efficiency, and core experiment 6 (CE6) in JVET is established to explore the transform-related coding tools. In this paper, we propose a novel signal-independent separable transform based on the Karhunen-Loève transform (KLT) to improve the efficiency of both intra and inter residual coding. In the proposed method, the drawbacks of the traditional KLT are addressed. A group of mode-independent intra transform matrices is calculated from abundant intra residual samples of all intra modes, while the inter separable KLT matrices are trained with the residuals that cannot be efficiently processed by the discrete cosine transform type II (DCT-II). The separable KLT is developed as an additional transform type apart from DCT-II. The experimental results show that the proposed method can achieve 2.7% and 1.5% bitrate saving averagely under All Intra and Random Access configurations on top of the reference software of VVC (VTM-1.1). In addition, the consistent performance improvement on test set also validates the property of signal independency and the strong generalization capacity of the proposed separable KLT.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Fan, Kui
Wang, Ronggang
Lin, Weisi
Duan, Ling-Yu
Gao, Wen
format Article
author Fan, Kui
Wang, Ronggang
Lin, Weisi
Duan, Ling-Yu
Gao, Wen
author_sort Fan, Kui
title Signal-independent separable KLT by offline training for video coding
title_short Signal-independent separable KLT by offline training for video coding
title_full Signal-independent separable KLT by offline training for video coding
title_fullStr Signal-independent separable KLT by offline training for video coding
title_full_unstemmed Signal-independent separable KLT by offline training for video coding
title_sort signal-independent separable klt by offline training for video coding
publishDate 2019
url https://hdl.handle.net/10356/106296
http://hdl.handle.net/10220/48882
http://dx.doi.org/10.1109/ACCESS.2019.2903734
_version_ 1681045806472232960