摘要
小波分析(Wavelet Analysis)在时域和频域内具有良好的局部化特性,被誉为信号分析的"数学显微镜"。笔者主要讲述小波变换在图像处理中的应用,介绍了小波分析的基础知识,包括一维连续小波变换、一维离散小波变换的基本原理,并由一维小波变换推广至二维小波变换,同时阐述小波变换应用于图像降噪、图像压缩、图像增强和图像融合中的基本原理及方法。
Wavelet analysis has good localization characteristics in both time domain and frequency domain, and is often called ＂mathematical microscope＂ for signal analysis.This paper mainly describes the application of wavelet transform in image processing. Firstly, the basic knowledge of wavelet analysis is introduced, including the basic principles of one-dimensional continuous wavelet transform and one-dimensional discrete wavelet transform, and extended from one-dimensional wavelet transform to two-dimensional wavelet transform. Then the basic principles and methods of wavelet transform applied in image denoising, image compression, image enhancement and image fusion are introduced.
作者
曹灿云
Cao Canyun(Guangdong University of Petrochemical Technology,Maoming Guangdong 525000,China)
出处
《信息与电脑》
2018年第18期114-115,121,共3页
Information & Computer
关键词
小波变换
图像降噪
图像压缩
图像增强
图像融合
wavelet transform
image denoising
image compression
image enhancement
image fusion
