改进的自适应中值滤波算法及其应用

摘要

针对自适应中值滤波在窗口迭代过程中存在像素点重复参与运算导致算法复杂度较高的问题,提出了一种改进的中值滤波算法.首先依据有效像素点与窗口中心点间的坐标距离来快速确定最佳滤波窗口尺寸,避免了窗口迭代造成的像素点重复排序;之后对窗口内的有效像素点进行取中值操作,有效削弱了噪声点的干扰,进一步提升了图像滤波的质量.经实验验证,与自适应中值滤波算法比较,复杂度显著降低,峰值信噪比(peak signal to noise ratio,PSNR)值平均提高10 dB左右.和同类文献比较在算法复杂度和图像降噪效果间做出了一个较佳的权衡.最后将该算法应用于Kinect深度图降噪上获得了不错的效果.%In this paper, an improved adaptive median filter algorithm was proposed to solve the problem of high complexity of adaptive median algorithm. First, the filter window size was determined according to the distance between the valid pixels and the center pixels in the proposed algorithm, which can avoid the waste of pixels repeated sort in window expand process. Second, the median value pixels were taken from valid pixels within the window by the improved algorithm, which effectively weakened the interference of noise point. The quality of image was improved compared with the original algorithm. This proposed algorithm reduced the complexity of algorithm and improved the effectiveness of noise reduction. The average PSNR value was increased 10 dB. Finally, the algorithm was applied to noise reduction with depth image captured from Kinect.