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A New Image Decomposition and Reconstruction Approach - Adaptive Fourier Decomposition

机译:一种新的图像分解与重构方法 - 自适应傅里叶分解

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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.
机译:傅立叶是一种强大的数学工具,用于表示信号中的信号组成的SIN和COS。 最近,Pro提出了一种新的发达信号分解理论。 陶谦命名为自适应傅里叶分解,这在傅里叶分解时具有时间频率的优势,而无需固定窗口大小问题,例如短时频率变换。 研究表明,AFD可以将信号快速分解成具有良好分析性质的正频功能。 在本文中,我们在文献中将AFD应用于图像分解和重建区域,这表明了有希望的结果,并给出了图像压缩的基本前景。

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