计算机技术与发展Issue(8)：250-253,4.DOI:10.3969/j.issn.1673-629X.2013.08.064
基于小波自适应阈值图像去噪方法的研究
Research on Image Denoising Based on Wavelet Adaptive Threshold
摘要
Abstract
Using wavelet transform to filter noises on image is a very effective method. The smoothing effect is not very good of tradition-al wavelet image denoising algorithm,and the image detail precision isn't high enough,even false Gibbs phenomenon can be produced. Aimming at the phenomenon,an improved multi-scale adaptive threshold method of image denoising based on wavelet transformation has been proposed. According to the characteristics of the image wavelet decomposition,this method can determine the better threshold of dif-ferent layers' coefficient for denoising after wavelet decomposition,then process the high frequency coefficient of each layer with appro-priate threshold function to achieve denoising effect. The experimental results show that,compared with traditional methods,this method can effectively remove Gaussian white noise and further improve the peak signal-to-noise ratio,while well preserving image details.关键词
图像去噪/小波变换/多尺度/自适应阈值/峰值信噪比Key words
image denoising/wavelet transform/multi-scale/adaptive threshold value/peak signal to noise ratio分类
信息技术与安全科学引用本文复制引用
于笃发,邵建华,张晶如..基于小波自适应阈值图像去噪方法的研究[J].计算机技术与发展,2013,(8):250-253,4.基金项目
江苏省科技计划资助项目(BK2010546) （BK2010546）
