一种改进的图像自适应非线性滤波方法

Improvement of Image Adaptive Nonlinear Filtering

针对图像的保边光滑问题,分析了Perona Malik(PM)方程的非线性滤波扩散行为,利用保边正则化思想给出了由一种新的各向异性扩散方程所决定的图像自适应光滑算法.这种新的各向异性扩散滤波方法与PM方程的不同之处在于:扩散系数不是直接来源于图像的梯度幅值,而是在图像梯度模基础上恢复出图像的边缘信息.实验结果表明,所提方法对图像边缘的恢复结果要比PM的方法具有更高的可靠性和准确性.

Based on the analysis of nonlinear diffusion of Perona-Malik (PM) equation, a nonlinear filtering method is proposed for image smoothing. The idea of edge-preserving regularization is introduced through a boundary intensity function. Compared with PM equation, the diffusion coefficient is not obtained from the gradient magnitude of the image directly, but the edge information (i.e. boundary intensity function) restored from the gradient magnitude based on the mode of the image. Experiments demonstrate that the proposed approach has better accuracy and reliability than PM for the results of edge restoration.