脉冲检测自适应模糊(IDAF)滤波器

H. Kam, W. Tan
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引用次数: 6

摘要

本文提出了一种脉冲检测自适应模糊(IDAF)滤波器,在保留图像细节的同时实现对脉冲噪声的改进滤波。它是一个空间过滤器,在2-stage 3x3窗口中运行,其中中心像素的更新值是窗口中像素的中值的函数。建议的IDAF过滤器的操作如下。首先,脉冲检测方法将每个像素分类为噪声像素或图像像素。然后,如果假设一个像素是有噪声的,它不用于确定其他像素的新值。介绍了一种获取良好的替换像素值的方案,并对其进行存储。存储值的中位数被认为是对图像像素的一个很好的估计。最后,自适应模糊滤波器将为存储的像素值分配权重,以产生中心像素的新值。根据像素的特性,分配权重以去除脉冲噪声或保留图像细节。这些特征是事先使用兼容性措施从噪声图像中识别出来的。上面详细介绍的过程使IDAF滤波器能够在保留图像细节的同时去除脉冲噪声。通过测试,我们的实验结果表明,IDAF滤波器的性能优于其他标准的基于中值的方法。
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Impulse Detection Adaptive Fuzzy (IDAF) Filter
An Impulse Detection Adaptive Fuzzy (IDAF) filter is proposed in this paper, to achieve improved filtering of impulsive noise while preserving image details. It is a spatial filter which operates in 2-stage 3x3 windows where the update value of the central pixel is a function of the median value of the pixels in the window. The proposed IDAF filter operates as follows. First, an impulse detection method classifies each pixel to be noisy pixel or image pixel. Then, if a pixel is assumed to be noisy, it is not used for deciding the new value of other pixels. A scheme is introduced to obtain a good replacement pixel value, which is then stored. The median of the stored values is a considered a good estimate of the image pixel. Finally, the adaptive fuzzy filter will then assign weights to the stored pixel values to produce the central pixel’s new value. Weights are assigned to remove impulse noise or preserve the image details, depending on the pixel’s characteristics. These characteristics are identified from the noisy image beforehand using a compatibility measure. The process detailed above enables the IDAF filter to remove impulse noise while preserving image details. Through testing, our experimental results show that the IDAF filter performs better than other standard median based methods.
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