基于一类集合算子的图象去噪方法及其快速实现

为了保留图象结构特征 ,消除图象中的脉冲型噪声 ,给出并讨论了一种基于单调集合算子的图象去噪方法 .该方法首先把原图象分解为一簇水平集 ,然后利用特定集合算子 ,对水平集进行滤波处理 ,最后用处理后的水平集重建图象 .该图象去噪方法同传统的中值滤波、高斯滤波相比 ,具有保形、保对比度的特点 .另外 ,为了提高图象去噪方法的效率 ,提出了一种基于 Heap数据结构的快速算法 ,此算法的效率要明显地高于逐次取阈值的方法 .实验结果表明 ,单调集合滤波算子 ,在去除脉冲噪声和保持图象结构与对比度方面具有独特的性能 ,同时给出的快速算法也是可行的

A Method of Image Denoising Based on Set Operator and its Fast Implementation

In order to eliminate impulse noise and preserve the fine structure features of the image, a method of the image denoising based on monotony set operator is presented. This method, firstly, uses the threshold decomposition principle to decompose the image into a bank of level sets, and then apply a special set operator to filter the level sets, finally restructure a image with the level sets filtered. To compare with traditional medial filter and Gaussian filter, the image denoising method based on set operator has the characteristics of shape preserving and contrast invariant. In addition, Fast algorithm based on Heap data structure is presented in order to increase the efficient of the filter algorithm. According to connection, the algorithm can find maximum and minimum regions, and if the area of the regions is less than a special value, then they will be cut. So the small peaks and small vales in the image can be eliminated. Experimental results show that the efficient of the algorithm is obvious over the method used one by one threshold, and set operator has remarkable advantages in terms of eliminating impulse noise, shape preserving and contrast invariant.