Recursive cubic spline interpolation filter approach for the removal of high density salt-and-pepper noise
Recursive cubic spline interpolation filter approach for the removal of high density salt-and-pepper noise
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DOI：
10.1007/s11760-013-0517-3
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发表时间：
2013-06
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影响因子：
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通讯作者：
Veerakumar Thangaraj;Esakkirajan Sankaralingam;I. Vennila
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文献类型：
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作者：
Veerakumar Thangaraj;Esakkirajan Sankaralingam;I. Vennila
提出了一种基于样条函数的方法来去除灰度图像和彩色图像中的高密度椒盐噪声。该算法由两个阶段组成，第一阶段检测像素是否有噪声或无噪声。第二阶段采用递归样条插值滤波器去除噪声像素点。本文提出的递归样条插值滤波器是基于邻域无噪声像素和前一个无噪声输出像素的，因此被称为递归样条插值滤波器。该算法的性能进行了比较，现有的算法，如标准的中值滤波器，基于决策的过滤器，渐进切换中值滤波器，和修改的基于决策的非对称修剪中值滤波器在非常高的噪声密度。该算法给出了更好的峰值信噪比，图像增强因子，和相关因子的结果比现有的算法。
Spline-based approach is proposed to remove very high density salt-and-pepper noise in grayscale and color images. The algorithm consists of two stages, the first stage detects whether the pixel is noisy or noise-free. The second stage removes the noisy pixel by recursive spline interpolation filter. The proposed recursive spline interpolation filter is based on the neighborhood noise-free pixels and previous noise-free output pixel; hence, it is termed as recursive spline interpolation filter. The performance of the proposed algorithm is compared with the existing algorithms like standard median filter, decision-based filter, progressive switched median filter, and modified decision-based unsymmetric trimmed median filter at very high noise density. The proposed algorithm gives better peak signal-to-noise ratio, image enhancement factor, and correlation factor results than the existing algorithms.