An Algorithm for Image Denoising Based on Mixed Filter

Yan-chun Wang, Dequn Liang, Heng Ma, Yan Wang
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引用次数: 17

Abstract

Generally, images can be corrupted by different characteristic noises simultaneously, we cannot obtain satisfactory filtering result if only using single filter such as average filter or median filter. Therefore, in this paper a new mixed filter algorithm is proposed for filtering the image corrupted by difference noises. Firstly, we construct adaptive structure using neighborhood contrast measure; secondly, divide the image into smoothness, edge and unconfirmed regions based on the adaptive structure; then, adopt corresponding filter for different regions. The algorithm does not need a priori knowledge of images and noises. We perform experiments on the image corrupted by Gaussian and impulse noises, by using average filter with maximization and minimization for the smoothness region, unidirectional median filter for the edge region and median filter for the indefinite region. The experiments show that the proposed algorithm is feasible and efficient
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一种基于混合滤波的图像去噪算法
通常情况下,图像会同时受到不同特征噪声的破坏,仅使用平均滤波器或中值滤波器等单一滤波器无法获得满意的滤波结果。为此,本文提出了一种新的混合滤波算法,用于滤波受差分噪声干扰的图像。首先利用邻域对比测度构建自适应结构;其次,基于自适应结构将图像划分为平滑区、边缘区和未确认区;然后,对不同的区域采用相应的滤波器。该算法不需要先验的图像和噪声知识。我们对被高斯噪声和脉冲噪声破坏的图像进行了实验,对平滑区域使用最大化和最小化的平均滤波器,对边缘区域使用单向中值滤波器,对不确定区域使用中值滤波器。实验证明了该算法的可行性和有效性
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