使用所有相邻方向加权像素的图像滤波：使用粒子群优化的优化
Image Filtering using All Neighbor Directional Weighted Pixels: Optimization using Particle Swarm Optimization
摘要：
本文提出了一种新的随机脉冲图像去噪方法。噪声抑制分两步进行。噪声像素的检测是使用5 x 5窗口中的所有相邻方向加权像素（ANDWP）来完成的。滤波方案是基于四个方向像素的最小方差。在这种方法中，相对较新的一类随机全局优化技术，即，粒子群优化（PSO）也被用于搜索最佳性能所需的检测和滤波算子的参数。结果表明，更好地去噪和保存的细节高度损坏的图像。
英文摘要：
In this paper a novel approach for de noising images corrupted by random valued impulses has been proposed. Noise suppression is done in two steps. The detection of noisy pixels is done using all neighbor directional weighted pixels (ANDWP) in the 5 x 5 window. The filtering scheme is based on minimum variance of the four directional pixels. In this approach, relatively recent category of stochastic global optimization technique i.e., particle swarm optimization (PSO) has also been used for searching the parameters of detection and filtering operators required for optimal performance. Results obtained shows better de noising and preservation of fine details for highly corrupted images.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
