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图像噪声方差的小波域估计算法
引用本文:李天翼,王明辉,吴亚娟,常化文.图像噪声方差的小波域估计算法[J].北京工业大学学报,2012,38(9):1402-1407.
作者姓名:李天翼  王明辉  吴亚娟  常化文
作者单位:四川大学计算机学院,成都,610065
基金项目:民航局科研基金资助项目
摘    要:为提高噪声方差估计准确度,在Donoho经典估计方法基础上,提出一种基于原始图像小波系数估计的算法.该算法通过挖掘小波尺度间的相关性,估计出原始图像小波系数,将含噪图像小波系数与之相减,得到较纯粹的噪声系数,再利用Donoho的方法进行估计.实验结果表明,该方法性能明显优于传统方法,尤其在噪声幅度较小或图像细节较丰富时性能表现更佳.

关 键 词:小波变换  方差估计  小波系数

Wavelet-based Approach for Estimating the Variance of Noise in Images
LI Tian-yi,WANG Ming-hui,WU Ya-juan,CHANG Hua-wen.Wavelet-based Approach for Estimating the Variance of Noise in Images[J].Journal of Beijing Polytechnic University,2012,38(9):1402-1407.
Authors:LI Tian-yi  WANG Ming-hui  WU Ya-juan  CHANG Hua-wen
Affiliation:(College of Computer Science,Sichuan University,Chengdu 610065,China)
Abstract:To improve the performance of the noise variance estimation,an algorithm based on the wavelet coefficients estimation of original image are proposed.Using the proposed approach,the authors exploited the inter-correlation of adjacent wavelet scales to estimate the wavelet coefficients of original image,thus got the purer noise coefficients by deducting the estimated values from the coefficients of the noisy image,then estimated once again using the Donoho's formula.Results show that the proposed approach outperforms traditional ones,especially in scenarios where there is less noise or much more image details.
Keywords:wavelet transform  variance estimation  wavelet coefficient
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