图像去噪:一种基于小波的方法

Rajib Guhathakurta
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引用次数: 7

摘要

由于小波变换在过去几十年中迅速普及,它已经成为许多研究和应用领域的标准工具。结合小波变换,介绍了各种小波域去噪算法。小波在图像去噪方面表现优异,因为它可以进行多分辨率分析。小波阈值法是一种利用小波变换进行信号去噪的信号估计技术。本计划的目的是研究各种不同的小波和小波包去噪技术,并比较它们,以确定较好的图像去噪技术。MSE和PSNR作为定量性能工具来比较各种去噪技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Denoising of image: A wavelet based approach
Owing to its rapidly increasing popularity over last few decades the wavelet transform has become quite a standard tool in numerous research and application domains. With Wavelet transforms, various algorithms for denoising in wavelet domain were introduced. Wavelets gave a superior performance in image denoising because here multi-resolution analysis is possible. Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. The aim of this project was to study various denoising techniques using wavelet and wavelet packets and compare them to determine the better one for image denoising. MSE and PSNR has been measured as quantitative performance tool to compare various denoising techniques.
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