Residential College | false |
Status | 已發表Published |
A new image decomposition and reconstruction approach -- adaptive Fourier decomposition | |
He C.2; Zhang L.2; He X.1; Jia W.1 | |
2015 | |
Source Publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Publisher | Springer, Cham. |
Pages | 227-236 |
Abstract | Fourier has been a powerful mathematical tool for representing a signal into an expression consist of sin and cos. Recently a new developed signal decomposition theory is proposed by Pro. Tao Qian named Adaptive Fourier Decomposition, which has the advantage in time frequency over Fourier decomposition and without the need for a fixed window size problem such as short-time frequency transform. Studies show that AFD can fast decompose signals into positive-frequency functions with good analytical properties. In this paper we apply AFD into image decomposition and reconstruction area first time in the literature, which shows a promising result and gives the fundamental prospect for image compression. |
Keyword | Adaptive Fourier Decomposition Image Compression Image Decomposition Mono-components Signal Processing |
URL | View the original |
Language | 英語English |
Volume | 8936 |
Fulltext Access | |
Document Type | Book chapter |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Corresponding Author | Zhang L. |
Affiliation | 1.University of Technology Sydney 2.Universidade de Macau |
First Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | He C.,Zhang L.,He X.,et al. A new image decomposition and reconstruction approach -- adaptive Fourier decomposition[M]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics):Springer, Cham., 2015, 227-236. |
APA | He C.., Zhang L.., He X.., & Jia W. (2015). A new image decomposition and reconstruction approach -- adaptive Fourier decomposition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8936, 227-236. |
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