基于自适应非线性扩散的局部二值模式图像去噪

Azizi Abdallah, Azizi Zineb
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引用次数: 1

摘要

非线性扩散方法是一种有效的去噪和保留边缘信息的方法。本文将工作扩展到整合非线性扩散和局部二值模式(LBP)文本,其中扩散函数适用于LBP分类后的像素类型。这允许平滑均匀和有噪声的区域,但不允许平滑边缘。该方法除了考虑4个最近邻外,还考虑了对角近邻的差异来控制扩散,从而更好地保留了边缘。在合成图像和真实图像上的实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Non-linear Diffusion Based Local Binary Pattern for Image Denoising
Non-linear diffusion approaches are an effective way to reduce noise and preserve the edge information. In this paper, the work is extended to integrate the non-linear diffusion and local binary pattern (LBP) textons, where the diffusivity function is adapted to pixels type after LBP classification. This allows smoothing on homogenous and noisy regions but not on edges. The proposed method preserves edges better because the diffusion is controlled taking into account the difference of diagonal neighbors in addition to four nearest neighbors. Experimental results on synthetic and real images illustrate the effective performance of the proposed method.
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