Highly Efficient Non-Separable Transforms for Next Generation Video Coding

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Said, Amir, Zhao, Xin, Karczewicz, Marta, Egilmez, Hilmi E., Seregin, Vadim, Chen, Jianle
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915308728483840
author Said, Amir
Zhao, Xin
Karczewicz, Marta
Egilmez, Hilmi E.
Seregin, Vadim
Chen, Jianle
author_facet Said, Amir
Zhao, Xin
Karczewicz, Marta
Egilmez, Hilmi E.
Seregin, Vadim
Chen, Jianle
contents For the last few decades, the application of signal-adaptive transform coding to video compression has been stymied by the large computational complexity of matrix-based solutions. In this paper, we propose a novel parametric approach to greatly reduce the complexity without degrading the compression performance. In our approach, instead of following the conventional technique of identifying full transform matrices that yield best compression efficiency, we look for the best transform parameters defining a new class of transforms, called HyGTs, which have low complexity implementations that are easy to parallelize. The proposed HyGTs are implemented as an extension of High Efficiency Video Coding (HEVC), and our comprehensive experimental results demonstrate that proposed HyGTs improve average coding gain by 6% bit rate reduction, while using 6.8 times less memory than KLT matrices.
format Preprint
id arxiv_https___arxiv_org_abs_2505_21728
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Highly Efficient Non-Separable Transforms for Next Generation Video Coding
Said, Amir
Zhao, Xin
Karczewicz, Marta
Egilmez, Hilmi E.
Seregin, Vadim
Chen, Jianle
Image and Video Processing
For the last few decades, the application of signal-adaptive transform coding to video compression has been stymied by the large computational complexity of matrix-based solutions. In this paper, we propose a novel parametric approach to greatly reduce the complexity without degrading the compression performance. In our approach, instead of following the conventional technique of identifying full transform matrices that yield best compression efficiency, we look for the best transform parameters defining a new class of transforms, called HyGTs, which have low complexity implementations that are easy to parallelize. The proposed HyGTs are implemented as an extension of High Efficiency Video Coding (HEVC), and our comprehensive experimental results demonstrate that proposed HyGTs improve average coding gain by 6% bit rate reduction, while using 6.8 times less memory than KLT matrices.
title Highly Efficient Non-Separable Transforms for Next Generation Video Coding
topic Image and Video Processing
url https://arxiv.org/abs/2505.21728