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Sliding Statistics Switching Median Filter for the Removalof Low Level Mix Impulse Noise

机译:滑动统计切换中值滤波器,用于去除低电平混合脉冲噪声

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摘要

A new nonlinearfiltering algorithm for effectively removing mix impulse noise in digital images, called twin sliding statistics switching median (TSSSM) filter is presented in this paper. The proposed TSSSM filter is made up of two subunits; i.e.impulse noise detection and noise filtering.At first,the impulse noise detection stage ofTSSSMalgorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order,concurrently. Next, the median of absolute difference (MAD) obtained from both statistics(i.e. sorted and non-sorted) will be further processed in order to classify any possible noise pixels.In addition, histogram based noise detector also used at this stage in order to increase the filter’s robustness. Subsequently, the filtering stage will replace the detected noise pixels with the estimatedmedian value of the surrounding pixels. Extensive simulations results conducted on grayscale images indicate that the TSSSM filter performs significantly better than a number of well-known impulse noise filters existing in literature in terms of noise suppression and detail preservation.
机译:提出了一种有效消除数字图像中混合脉冲噪声的新型非线性滤波算法,称为双滑动统计切换中值(TSSSM)滤波器。提出的TSSSM滤波器由两个子单元组成;首先,TSSSM算法的脉冲噪声检测阶段开始于同时处理已排序的和未排序的局部检测窗口的统计信息。接下来,将从两个统计数据(即已排序和未排序)中获得的绝对差的中值(MAD)进行进一步处理,以对任何可能的噪声像素进行分类。此外,在此阶段还使用了基于直方图的噪声检测器,以便提高滤波器的鲁棒性。随后,滤波阶段将用周围像素的估计中值替换检测到的噪声像素。在灰度图像上进行的广泛仿真结果表明,在噪声抑制和细节保留方面,TSSSM滤波器的性能明显优于文献中存在的许多众所周知的脉冲噪声滤波器。

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