改进的NAS-RIF图像盲复原算法  

An Improved NAS-RIF Algorithm for Image Restoration

作　　者：李红丽[1] 马耀锋[1] 

机构地区：[1]中州大学信息工程学院,郑州450004

出　　处：《电光与控制》2013年第4期31-33,共3页Electronics Optics & Control

基　　金：河南省教育厅自然科学基金(2010C520020)

摘　　要：针对非负和支持域受限递归逆滤波算法(NAS-RIF)的缺点,提出了一种改进方案。首先,引入高阶统计量去噪,解决了NAS-RIF算法敏感于噪声的特性;其次,利用图像分割技术进行图像支持域的自估计,改变了NAS-RIF算法中支持域必须是方形的不利限制;最后,运用该算法对不同峰值信噪比(PSNR)和背景的含噪图像进行了算法仿真,并与原算法进行了比较。仿真结果表明,改进的NAS-RIF算法有效解决了原始算法中存在的问题,显著提高了恢复图像的质量。An improved method is presented to overcome the drawbacks of the original NAS-RIF algorithm. To deal with the noise sensitivity Of NAS-RIF, higher order statistics denoising was introduced. To solve the problem that the NAS-RIF requires square support region, the image segmentation based self-estimation of image support region was used. At last, simulation was made to various PSNR images and backgrounds. The improved algorithm was compared with the original one. The simulation results show that the improved algorithm solves the problems of the original algorithm, and can improve the quality of recovery image observably.

关 键 词：图像处理 图像盲恢复 高阶统计量 支撑域估计 NAS—RIF算法 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]