结合区域分割和双边滤波的图像去噪新算法

New filter based on region segmentation and bilateral filtering

提出一种结合区域分割和双边滤波的图像高斯噪声抑制新算法。基于像素的双边滤波器在滤波时,由于平滑系数的选择受到噪声的干扰,在图像边缘区域的滤波存在一定的盲目性,导致滤波结果中结构信息不能有效保持。本文在图像分割的基础上利用区域图来指导双边滤波过程,根据区域内的噪声属性和区域间的相似程度来分别计算相应像素间的滤波平滑系数。通过对区域内与区域间进行不同模式的滤波,增强了滤波算法对图像结构的自适应性。实验结果表明,该算法在获得良好去噪效果的同时,能有效保持图像的结构信息。

In this paper, we present a new algorithm to remove Gaussian noise in images by combining region segmentation and bilateral filtering. The pixel-based bilateral filter suffers difficulties in an appropriate selection of the smoothing parameter due to the disturbance of noise, which poses obstacles to the filtering process in dealing with edges and hence degrades the preservation of image structures. Based on the segmentation of images, this work takes advantage of the region map to facilitate the filtering process. Specifically, noise characteristics within regions and similarities between regions are utilized to derive smoothing parameters corresponding to the involved pixels. By applying filtering to pixels within regions and between regions in different means, the algorithm gains enhanced adaptability to image structures. Relative to some existing bilateral filter algorithms, testing results have demonstrated that the proposed algorithm improved the de-noising performance especially on the preservation of structure information.