一种改进的非负限定性支持域算法  

An improved NAS-RIF algorithm

作　　者：刘宁[1] 楼顺天[1] 

机构地区：[1]西安电子科技大学电子工程学院,陕西西安710071

出　　处：《西安电子科技大学学报》2007年第2期246-248,269,共4页Journal of Xidian University

基　　金：国家自然科学基金资助项目(60072043)

摘　　要：引入单调平滑的对数函数,对原代价函数取以e为底的对数进行复合,提出了一种改进的非负限定性支持域算法.从代价函数的梯度入手推导出共轭梯度算法,其搜索方向保持不变而搜索步长变小,使滤波系数更加逼近于点扩展函数逆算子,从而使估计图像与原始图像更加接近.对文字模糊图像的仿真结果表明,与原始算法相比,改进算法的均方误差曲线收敛性及稳定性更好,提高了恢复图像的信噪比.By introducing the monotone smooth logarithm and compounding it with the original cost function, we propose an improved nonnegativity and support constraints recursive inverse filtering algorithm （NAS-RIF） for image restoration. It has been deduced that the search direction remains the same but that the step length decreases in optimizing the improved cost function with the conjugate gradient algorithm from the gradient of the cost function that the FIR filter apporaches the contrary point spread function （PSF） more, and that the estimated image is closer to the original one. The experiment on a blurred text image restoration shows that the mean square error（MSE） of the improved NAS-RIF algorithm has a better convergence, and that the signal to noise ratio is improved.

关 键 词：非负限定性支持域算法 盲图像恢复 对数函数 梯度 

分 类 号：TN911.73[电子电信—通信与信息系统]