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Adaptive Four-dot Median Filter for Removing 1-99% Densities of Salt- and-Pepper Noise in Images

机译:自适应四点中值滤波器,去除图像中盐和胡椒粉噪声的1-99%

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摘要

In order to accelerate denoising and improve the denoising performance of the current median filters, an Adaptive Four-dot Median Filter (AFMF) for image restoration is proposed in this article. AFMF is not only very efficient and fast in logic execution, but also it can restore the corrupted images with 1–99% densities of salt-and-pepper noise to the satisfactory ones. Without any complicated operation for noise detection, it intuitively and simply distinguishes impulse noises, while keeping the noise-free pixels intact. Only the uncorrupted pixels of the four-dot mask in adaptive filtering windows are used for the adoption of candidates for median finding, whatever filtering window size is. Furthermore, the adoption of recursive median filters leads to denoising performance improvement and faster filtering. The simple logic of the proposed algorithm obtains significant milestones on the fidelity of a restored image. Relevant experimental results on subjective visualization and objective digital measure validate the robustness of the proposed filter.
机译:为了加速去噪并提高当前中值滤波器的去噪性能,本文提出了一种用于图像恢复的自适应四点中值滤波器(AFMF)。 AFMF不仅在逻辑执行方面非常高效且快速,而且还可以将椒盐噪声的1–99%密度还原为令人满意的图像。它无需任何复杂的噪声检测操作,就可以直观,简单地区分脉冲噪声,同时保持无噪声像素的完整性。无论过滤窗口的大小如何,自适应过滤窗口中只有四点掩模的未损坏像素才可用于中值查找的候选对象。此外,采用递归中值滤波器可降低性能并降低滤波速度。所提出算法的简单逻辑在还原图像的保真度上获得了重要的里程碑。有关主观可视化和客观数字测量的相关实验结果验证了所提出滤波器的鲁棒性。

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