应用改进自蛇模型和L-R算法恢复毫米波图像

在毫米波的图像恢复中,L-R算法是一种简单而有效的非线性方法,但当噪声不可忽略时,L-R算法难以获得较好的复原结果。针对毫米波图像数据量少和图像分辨率低的特点,提出基于改进自蛇模型和L-R算法毫米波图像恢复方法,以局部方差构造自蛇模型的边缘停止函数,其改进自蛇模型在消除噪声的同时更能够保留图像中的边缘和细节特征,然后使用L-R算法进行图像恢复,这种改进算法通过使用基于改进自蛇模型去噪能有效地减少噪声对L-R算法的影响。实验结果表明:在信噪比和相关度方面本文算法提高了L-R算法的性能,可用于含噪声的图像复原。

Millimeter wave image restoration based on the improved self-snake model and L-R algorithm

In millimeter wave image restoration,L-R(Lucy-Richardson)algorithm is a simple and effective nonlinear method.However,when the noise can not be neglected,it is difficult for L-R algorithm to get good restoration.As an improved self-snake model has a merit of maintaining image edge and features and can de-noise effectively for the millimeter wave image having fewer data and lower resolution,a novel restoration method is proposed based on the improved self-snake model and L-R algorithm.It first de-noises by employing the improved self-snake model which edge stopping function is made of local variance,and then restores images by using L-R algorithm.The modified algorithm reduces the influence of noise on L-R algorithm effectively by using de-noise algorithm based on the improved self-snake model.The imaging results of experiment data show that the modified algorithm proposed in the paper improves the L-R algorithm performances of the signal to noise ratio and relevance,and it can be used in millimeter wave image with much noises.