Abstract

This paper focuses on the removal of salt and pepper noise from a contaminated image. A Probabilistic Decision Based Improved Trimmed Median Filter (PDITMF) is proposed here. The proposed PDITMF algorithm resolves the conflict regarding an even number of noise free pixel of Trimmed Median Filter. The proposed algorithm makes use of two estimation techniques for de-noising, namely, Improved Trimmed Median Filter (ITMF), and Patch Else Improved Trimmed Median Filter (PEITMF) depending upon noise density. The algorithm experiments with many standard sample images. Simulation results show the proposed algorithm is capable of de-noising the image very efficiently. The algorithm has a better visual representation and it outperforms the existing well-known algorithms in context to peak signal-to-noise ratio (PSNR) as well as image enhancement factor (IEF) with lower execution time (ET) at all noise densities.

中文翻译：

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基于概率决策的改进修剪中值滤波器，去除高密度盐和胡椒噪声

摘要

本文着重于去除污染图像中的盐和胡椒粉噪声。本文提出了一种基于概率决策的改进的中值滤波算法（PDITMF）。提出的PDITMF算法解决了与修剪后的中值滤波器的偶数个无噪声像素有关的冲突。所提出的算法利用两种估计技术来进行降噪，即，根据噪声密度，改进的修剪中值滤波器（ITMF）和补丁其他改进的修剪中值滤波器（PEITMF）。该算法使用许多标准样本图像进行实验。仿真结果表明，该算法能够非常有效地对图像进行消噪。