基于不可分离小波和SURE-LET的图像去噪

W. Zeng, Xiubao Jiang, Zhengquan Xu, Long Zhou
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引用次数: 2

摘要

本文提出了一种基于不可分小波的图像去噪方法。与传统的可分离小波滤波器组限制了捕获方向信息的能力不同,不可分离小波滤波器组包含面向各种方向的基元,能够捕获不同的细节信息。使用SURE-LET无需为无噪声图像假设统计模型。另外,SURE-LET去噪算法仅仅相当于求解线性方程组,速度快、效率高。实验结果表明,基于不可分离小波的SURE-LET去噪方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Denoising Using Nonseparable Wavelet and SURE-LET
In this paper, we present a novel method to image denoising using non-separable wavelet based SURE-LET approach. Unlike conventional separable wavelet filter banks that limit the ability in capturing directional information, non-separable wavelet filter banks contain the basis elements oriented at a variety of directions which are able to capture different detail information. Using SURE-LET makes it needless to hypothesize a statistical model for the noiseless image. Besides, SURE-LET denoising algorithm merely amounts to solving linear system of equations, which is obviously fast and efficient. Experimental results on several test images are compared with separable wavelet based denoising techniques, the competitive results show that the non-separable wavelet based SURE-LET method is effective.
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