Advanced video coding based on matrix decomposition
Video coding has been widely used in everyday work and life. Most of the video coding technologies are based on a set of principles that reduce the redundancy in digital video, including mainly temporal, spatial and statistical redundancies. In this study, we explore new methodology for further r...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2014
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/55344 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-55344 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-553442023-03-04T00:45:40Z Advanced video coding based on matrix decomposition Gu, Zhouye Lin Weisi School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory Video coding has been widely used in everyday work and life. Most of the video coding technologies are based on a set of principles that reduce the redundancy in digital video, including mainly temporal, spatial and statistical redundancies. In this study, we explore new methodology for further redundancy reduction. Combining the matrix decomposition algorithms, we have proposed three matrix decomposition based techniques that further enhance compression performance, when compared with the relevant state of the art technology. Firstly, we propose a temporal redundancy reduction scheme based upon Two-Dimensional Singular Value Decomposition (2D-SVD) without resorting to motion estimation (ME). Its computational complexity is much lower than that of ME-based video coding scheme. By exploring the energy compaction property of 2D-SVD coefficient matrices, high coding efficiency is achieved compared with other non-ME based methods. Secondly, for spatial redundancy reduction, the existing video codecs use Discrete Cosine Transform (DCT), which is originally designed based on the spatial characteristic of natural image pixels, for predicted residual pixels compression; Since the spatial characteristic of predicted residual pixels differs from that of natural image pixels, we develop a new orthogonal transform—Rotated Orthogonal Transform (ROT) that yields better compression on the prediction residual than the DCT. Lastly, for statistical redundancy reduction, the entropy coders that originally designed for lossy video coding are also used for lossless video coding in the current standard video coding scheme. Since the coefficients generated by lossy and lossless coding processes have different statistical distributions, we therefore propose a new methodology based on Mode Dependent Template (MD-Template) and scan order for better intra lossless video coding. The algorithms proposed in this thesis are developed from three different matrix decomposition problems. The have been validated on a large number of standard video sequences. We have performed careful experimental analysis and demonstrated that the proposed techniques overall perform better than the existing relevant methods. DOCTOR OF PHILOSOPHY (SCE) 2014-02-11T06:29:03Z 2014-02-11T06:29:03Z 2012 2012 Thesis Gu, Z. (2012). Advanced video coding based on matrix decomposition. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/55344 10.32657/10356/55344 en 143 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory |
spellingShingle |
DRNTU::Engineering::Computer science and engineering::Data::Coding and information theory Gu, Zhouye Advanced video coding based on matrix decomposition |
description |
Video coding has been widely used in everyday work and life. Most of the video coding technologies are based on a set of principles that reduce the redundancy in
digital video, including mainly temporal, spatial and statistical redundancies. In this study, we explore new methodology for further redundancy reduction. Combining the matrix decomposition algorithms, we have proposed three matrix decomposition based techniques that further enhance compression performance, when compared with the
relevant state of the art technology.
Firstly, we propose a temporal redundancy reduction scheme based upon Two-Dimensional Singular Value Decomposition (2D-SVD) without resorting to motion estimation (ME). Its computational complexity is much lower than that of ME-based
video coding scheme. By exploring the energy compaction property of 2D-SVD coefficient matrices, high coding efficiency is achieved compared with other non-ME based methods.
Secondly, for spatial redundancy reduction, the existing video codecs use Discrete Cosine Transform (DCT), which is originally designed based on the spatial characteristic of natural image pixels, for predicted residual pixels compression; Since the spatial characteristic of predicted residual pixels differs from that of natural image pixels, we develop a new orthogonal transform—Rotated Orthogonal Transform (ROT) that yields better compression on the prediction residual than the DCT.
Lastly, for statistical redundancy reduction, the entropy coders that originally designed for lossy video coding are also used for lossless video coding in the current standard video coding scheme. Since the coefficients generated by lossy and lossless
coding processes have different statistical distributions, we therefore propose a new methodology based on Mode Dependent Template (MD-Template) and scan order for
better intra lossless video coding.
The algorithms proposed in this thesis are developed from three different matrix decomposition problems. The have been validated on a large number of standard video sequences. We have performed careful experimental analysis and demonstrated that the proposed techniques overall perform better than the existing relevant methods. |
author2 |
Lin Weisi |
author_facet |
Lin Weisi Gu, Zhouye |
format |
Theses and Dissertations |
author |
Gu, Zhouye |
author_sort |
Gu, Zhouye |
title |
Advanced video coding based on matrix decomposition |
title_short |
Advanced video coding based on matrix decomposition |
title_full |
Advanced video coding based on matrix decomposition |
title_fullStr |
Advanced video coding based on matrix decomposition |
title_full_unstemmed |
Advanced video coding based on matrix decomposition |
title_sort |
advanced video coding based on matrix decomposition |
publishDate |
2014 |
url |
https://hdl.handle.net/10356/55344 |
_version_ |
1759857011168641024 |