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首页> 外文期刊>The mediterranean journal of electronics and communications >IMPULSE NOISE SUPPRESSION USING OPTIMAL DIRECTION METHOD AND NON-LOCAL MEANS FILTER
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IMPULSE NOISE SUPPRESSION USING OPTIMAL DIRECTION METHOD AND NON-LOCAL MEANS FILTER

机译：最优方向和非局部均值滤波的脉冲噪声抑制

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摘要

Impulse noise removal process from digital images is one of the most important concerns in digital image processing. Impulsive noise may occur during image acquisition, transmission or storagewhich is often not possible to avoid in practical situations. The noise should be removed in such a way that important information of image should be preserved. The restoration process of many known algorithms are effective for the images corrupted by random valued impulse noise, but not efficient especially for real-time applications. In this paper, we propose an efficient impulse noise suppression technique using optimal direction based noised detection followed by non-local mean filtering. The optimal direction is the direction that has the most similar pixels, is obtained by comparing the standard deviation of four directions of the detection window. More edge pixels can be detected if the accurate or optimal direction of the edge is determined. The normalized distance between original pixel and other pixels in the optimal direction i.e. Normalized Distance in Optimal Direction (NDOD) is used as a statistical measure to detect impulse noise in an image. It measures how different a tested pixel from the pixels present in optimal direction of the window. For noise filtering, an impulse noise filter is proposed here by combining the NDOD statistic with the Non-Local Means (NLM). The noisy pixels are replaced by weighted average of neighboring pixels, where the weight shows the contribution of the neighboring pixels in filtering. The filtered result is compared with the other recent approaches in terms of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measures (SSIM). Extensive simulations show that the proposed technique has superior performance in terms of both visual quality and quantitative measurement.
机译：从数字图像中去除脉冲噪声的过程是数字图像处理中最重要的问题之一。脉冲噪声可能会在图像获取，传输或存储过程中发生，在实际情况下通常无法避免。应以保留图像的重要信息的方式消除噪点。许多已知算法的恢复过程对于被随机值的脉冲噪声破坏的图像是有效的，但是对于实时应用尤其无效。在本文中，我们提出了一种有效的脉冲噪声抑制技术，该方法采用基于最优方向的噪声检测，然后进行非局部均值滤波。最佳方向是像素数量最多的方向，是通过比较检测窗口四个方向的标准偏差获得的。如果确定边缘的准确或最佳方向，则可以检测到更多的边缘像素。原始像素和其他像素在最佳方向上的归一化距离，即最佳方向上的归一化距离（NDOD），用作检测图像中脉冲噪声的统计量。它测量被测像素与窗口最佳方向上存在的像素之间的差异。对于噪声滤波，这里通过结合NDOD统计数据和非局部均值（NLM）提出了脉冲噪声滤波器。噪点像素被相邻像素的加权平均值代替，其中权重显示了相邻像素在滤波中的贡献。将滤波后的结果与峰值信噪比（PSNR）和结构相似性指标度量（SSIM）方面的其他最新方法进行比较。大量的仿真表明，该技术在视觉质量和定量测量方面均具有出色的性能。

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