图像恢复的正则化Gmres方法

在处理具有线性的、空间位移不变的成像系统所成的图像恢复问题时，提出了一种基于Krylov向量完全正交化的正则化Gmres方法。该算法考虑了图像恢复中的不适定性及计算时的复杂性两个方面，将正则化算法与广义极小残余算法相结合，通过正则化方法将模型离散后的积分方程转化为一适定问题，然后利用广义极小残余算法得到结果。在数值模拟时，对不同的方法进行了对比分析，结果表明所选的方法能够明显改善图像恢复的质量。

Regularized Gmres method of image restoration

Dealing with the restoration problem of image through the linear, spatial displacement of the imaging system, a completely orthogonal regularization Gmres method based on Krylov vectors was proposed. The proposed algorithm considered the ill-posedness in image restoration and the complexity of the calculation, and combined the regularization algorithm with the generalized minimal residual algorithm. By introducing the regularization method, the discredited integral equation was transformed into a posed problem of discrete and the numerical solution was obtained by generalized minimal residual algorithm. In the numerical simulation, the different methods were compared. The experimental results show that the proposed method can significantly improve the quality of image restoration.