基于脉冲噪声抑制的新型鲁棒RM-KNN滤波器

V. Ponomaryov, A.B. Pogrebniak, F. Gonzales Leon
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引用次数: 1

摘要

我们介绍了适用于图像处理的新型鲁棒滤波算法。它们是通过使用rm型点估计和众所周知的约束技术推导出来的,特别是用于图像处理的KNN滤波器。导出的RM-KNN滤波器有效地去除脉冲噪声,同时保留边缘和精细细节。在模拟图像和真实成像雷达数据上进行了测试,与标准中值滤波器相比,所提出的滤波器具有良好的视觉质量和定量质量。给出了适当选择衍生滤波器参数以获得最佳处理结果的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel robust RM-KNN filters with impulsive noise suppression for image processing
We introduce novel robust filtering algorithms applicable to image processing. They are derived by use of RM-type point estimations and the restriction technique of the well-known, specifically for image processing, KNN filter. The derived RM-KNN filters effectively remove impulsive noise while edge and fine details are preserved. The proposed filters are tested on simulated images and real imaging radar data and provide excellent visual quality of the processed images and good quantitative quality in comparison with the standard median filter. Recommendations to obtain the best processing results by proper selection of derived filter parameters are given.
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