Super-resolution Image Reconstruction Based on Sequence of Subset Conjugate Graduate Optimization

A sequence of subset conjugate graduate optimization based super-resolution algorithm is proposed for super-resolution,where image registration algorithm is used to estimate the displacement and rotation between different low-resolution images,prior knowledge is used for regulation and building the cost function,and the high-resolution image is estimated by using sequence subset conjugate graduate optimization algorithm.Simulation results demonstrate that the method can realize the super-resolution with 15% memory reduction and 20% high speed promotion.