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Novel robust rank KNN filters with impulsive noise su

机译:具有脉冲噪声的新型鲁棒秩KNN滤波器

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Abstract: Novel robust filtering algorithms applicable to image processing are introduced. They were derived using robust M- type point estimators and the restriction technique of the well-known KNN filter. The derived filters effectively remove impulse noise and preserve edge and fine details. The proposed filters provide excellent visual quality of the processed simulated images and good quantitative quality in the MSE sense in comparison to the standard median filter. Recommendations to obtain best processing results by proper selection of derived filter parameters are given. Two derived filters are suitable for impulse noise reduction in any image processing applications. One can use the RM-KNN filters at the first stage of image enhancement followed by any detail-preserving techniques such as the Sigma filter at the second stage.!19
机译:摘要:介绍了适用于图像处理的新型鲁棒滤波算法。它们是使用鲁棒的M型点估计器和著名的KNN滤波器的限制技术得出的。派生的滤波器可有效消除脉冲噪声并保留边缘和精细细节。与标准中值过滤器相比,所提出的过滤器在MSE意义上提供了出色的处理后的模拟图像视觉质量和良好的定量质量。给出了通过适当选择导出的滤波器参数以获得最佳处理结果的建议。两个派生的滤波器适用于任何图像处理应用中的脉冲噪声降低。可以在图像增强的第一阶段使用RM-KNN过滤器,然后在第二阶段使用诸如Sigma过滤器之类的任何细节保留技术。!19

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