Image Salt & Pepper Noise Self-adaptive Suppression Algorithm Based on Similarity Function
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摘要: 在分析现有的细节保护滤波算法的基础上,提出了一种基于相似度函数的自适应权重滤波算法. 主要技术包括分析 Maximum-minimum 椒盐噪声检测算子的局部极值误判缺陷, 并利用具有良好细节保护特性的相似度函数自适应权重算法来解决这一问题. 在滤波过程中采用极值剪切操作来估计图像的局部噪声密度, 用来选择合适形式的滤波窗口(递归或非递归), 从而利用单一的 3×3 滤波窗口就实现了对不同密度椒盐噪声的自适应有效去除. 实验表明, 该算法的噪声滤除能力、细节保护能力以及运算效率都可以得到满意的结果.Abstract: Through summarizing the existing detail-preserving salt pepper noise suppression methods, a new similarity function self-adaptive weighted algorithm is proposed. It analyzes and overcomes the shortcoming of the local extremum misjudgment of the Maximum-minimum noise detector by using a similarity function self-adaptive weighted algorithm. The local window noise probability is estimated by applying extremum trimming operation to select a suitable filtering window (recursive window or non-recursive window). Thus the proposed algorithm realizes self-adaptive suppression of different salt pepper noise probabilities using a 3×3 filtering window. Experiments show that the results of salt pepper noise suppression, detail-preserving and computation efficiency are satisfactory.
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