摘要
给出了一种用于图像盲复原的基于非负支撑域受限递归逆滤波 (NAS-RIF)算法的改进算法。通过在代价函数中加入空间自适应的正则化项来改进算法的抗噪性能和复原效果 ,并利用迭代算法的中间结果 ,进一步精确寻找图像边界 ,有效地达到了保存边界并抑制噪声的目的。使用 n步重新开始的共轭梯度法可以提高算法的收敛速度。由实验结果可以看出 ,对于信噪比较低的退化图像 ,改进的 NAS-RIF算法具有更好的复原效果和稳定性。
An improved nonnegativity and support constraints recursive inverse filtering (NAS RIF) algorithm for blind image restoration is proposed, in which the noise resistance ability and the restoration effect are developed by adding a space adaptive regularization. Using the intermediate product of the iteration to find precise space information of the image, the improved NAS RIF algorithm works well in preserving the edges and restraining noise amplification. N step restart conjugate gradient routine is used to speed up the convergence rate. Experimental results show that the improved NAS RIF algorithm provides a better restoration result and is more stable especially under low SNR conditions.
出处
《数据采集与处理》
CSCD
2002年第2期121-125,共5页
Journal of Data Acquisition and Processing
基金
国家自然科学基金 (编号 :69972 0 1 2 )
教育部骨干教师基金资助项目
