Constrained variable projection method for blind deconvolution
Constrained variable projection method for blind deconvolution
复制标题
盲反卷积的约束变量投影方法
DOI：
10.1088/1742-6596/386/1/012005
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
James G. Nagy
中科院分区：
文献类型：
--
作者：
A. Cornelio;E. L. Piccolomini;James G. Nagy
本文将盲解卷积问题归结为一个可分离的非线性最小二乘问题。无论是恢复模糊算子还是恢复真实图像，都存在众所周知的不适定性，这使得这个问题很难处理。我们表明，通过对变量施加适当的约束并选择适当的正则化参数，可以获得行为相当良好的目标函数。因此，所得到的非线性极小化问题可以用经典的方法有效地求解，如高斯-牛顿算法。
This paper is focused on the solution of the blind deconvolution problem, here modeled as a separable nonlinear least squares problem. The well known ill-posedness, both on recovering the blurring operator and the true image, makes the problem really difficult to handle. We show that, by imposing appropriate constraints on the variables and with well chosen regularization parameters, it is possible to obtain an objective function that is fairly well behaved. Hence, the resulting nonlinear minimization problem can be effectively solved by classical methods, such as the Gauss-Newton algorithm.