基于MG-CG算法的图像超分辨率重建

提出一种基于多重网格(MG)和共扼梯度(CG)算法相结合的图像超分辨率重建快速算法.首先采用Tikhonov正则化方法给出图像超分辨率重建模型;然后在系统介绍MG和CG算法的基础上,针对超分辨率重建中常见对称正定稀疏线性方程的求解,提出多重网格-共扼梯度(MG-CG)算法;详细讨论了MG-CG算法的光滑、限制、插值操作以及计算复杂度.实验结果表明该算法与MG、CG和Richardson迭代算法相比,具有更快的收敛速度.

Image Super-Resolution Reconstruction Based on MG-CG Algorithm

A fast image super-resolution reconstruction algorithm is proposed based on multigrid(MG)and conjugate gradient(CG)algorithms.Firstly,the image super-resolution reconstruction model is put forward using Tikhonov regularization.After systemically introduction of MG and CG algorithms,an accelerative MG algorithm named MG-CG is proposed to solve the sparse symmetric positive linear equation,which is often occurred in image super-resolution reconstruction.The smooth,restriction and interpolation operators are thoroughly studied and the computational complexity is analyzed in detail.Experimental results demonstrate that the proposed algorithm can greatly improve the speed of convergence compared with MG,CG,and Richardson iteration.