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A new image decomposition and reconstruction approach -- adaptive Fourier decomposition
He C.2; Zhang L.2; He X.1; Jia W.1
2015
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer, Cham.
Pages227-236
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.

KeywordAdaptive Fourier Decomposition Image Compression Image Decomposition Mono-components Signal Processing
URLView the original
Language英語English
Volume8936
Fulltext Access
Document TypeBook chapter
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorZhang L.
Affiliation1.University of Technology Sydney
2.Universidade de Macau
First Author AffilicationUniversity 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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