UM  > Faculty of Science and Technology
Affiliated with RCtrue
Status已發表Published
Image Compression Using Stochastic-AFD Based Multi-signal Sparse Representation
Dai L.1; Zhang L.1; Li H.2
2022-08
Source PublicationIEEE Transactions on Image Processing
ISSN1057-7149
Volume31Pages:5317 - 5331
Abstract

Adaptive Fourier decomposition (AFD) is a newly developed signal processing tool that can adaptively decompose any single signal using a Szegö kernel dictionary. To process multiple signals, a novel stochastic-AFD (SAFD) theory was recently proposed. The innovation of this study is twofold. First, a SAFD-based general multi-signal sparse representation learning algorithm is designed and implemented for the first time in the literature, which can be used in many signal and image processing areas. Second, a novel SAFD based image compression framework is proposed. The algorithm design and implementation of the SAFD theory and image compression methods are presented in detail. The proposed compression methods are compared with 13 other state-of-the-art compression methods, including JPEG, JPEG2000, BPG, and other popular deep learning-based methods. The experimental results show that our methods achieve the best balanced performance. The proposed methods are based on single image adaptive sparse representation learning, and they require no pre-training. In addition, the decompression quality or compression efficiency can be easily adjusted by a single parameter, that is, the decomposition level. Our method is supported by a solid mathematical foundation, which has the potential to become a new core technology in image compression.

DOI10.1109/TIP.2022.3194696
URLView the original
Indexed BySCIE
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorZhang L.
Affiliation1.University of Macau
2.Huazhong University of Science and Technology
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Dai L.,Zhang L.,Li H.. Image Compression Using Stochastic-AFD Based Multi-signal Sparse Representation[J]. IEEE Transactions on Image Processing,2022,31:5317 - 5331.
APA Dai L.,Zhang L.,&Li H..(2022).Image Compression Using Stochastic-AFD Based Multi-signal Sparse Representation.IEEE Transactions on Image Processing,31,5317 - 5331.
MLA Dai L.,et al."Image Compression Using Stochastic-AFD Based Multi-signal Sparse Representation".IEEE Transactions on Image Processing 31(2022):5317 - 5331.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Dai L.]'s Articles
[Zhang L.]'s Articles
[Li H.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Dai L.]'s Articles
[Zhang L.]'s Articles
[Li H.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Dai L.]'s Articles
[Zhang L.]'s Articles
[Li H.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.