基于局部方差的自蛇模型平滑毫米波图像

An Improved Self-snake Model Based on Local Variance for Millimeter-wave Smoothing

针对毫米波图像数据量少和图像分辨率低的特点,提出基于局部方差自蛇模型平滑毫米波图像的方法.3×3窗口内的局部方差使毫米波图像在边缘和细节附近,其边缘停止函数接近为0,执行较小的平滑;在区域内部其边缘停止函数接近为1,进行较大的平滑,从而能够自适应地控制平滑过程.实验结果表明,所提出的平滑方法与传统自蛇模型相比,在消除噪声的同时更能够保留图像中的边缘和细节特征.

Due to the major drawback of the millimeter-wave image having a fewer data and lower resolution,an improved self-snake model based on local variance is proposed for its smoothing.This method uses the local variance of window 3×3 to construct edge stopping function that is approximated to zero around fine structures and is close to one in the interior of homogeneous regions.Here the filtering process could be better control by constraining smoothing in regions with fine details while permitting effective smoothing in the interior of homogeneous.Comparative experiments certify that the proposed algorithm outperforms the corresponding conventional self-snake methods in terms of noise removal and feature preservation.