基于二阶广义全变差的多帧图像超分辨率重建

图像超分辨率重建是图像处理领域的重要问题.本文将二阶广义全变差用于基于正则化的多帧图像超分辨率重建问题,构建了基于二阶广义全变差正则项的图像超分辨率模型.为了更好地保持重建图像的边缘和细节,采用图像空域自适应正则化参数,并针对该重建模型的非光滑性,给出了基于半二次正则化和交替方向法的求解算法.实验结果表明该模型和数值算法能够较好地提高图像的分辨率,同时可以较好地保持图像的细节信息.

Multiframe Image Super Resolution Based on Second Order Total Generalized Variation

Super resolution is a very important issue in the field of image processing.In this paper,Second order total general variation (TGV) is used to solve a reconstruction based multi-frame images super resolution problem.A second order total general variation based super resolution model is built in the paper.In order to preserve the edges and detail information,a spatial adaptive regularization parameter of the image is applied.For solving the non-smooth problem,a half quadric and alternating direction based numerical algorithm is proposed.Experiments verified that the proposed model and numerical algorithm can effectively increase the resolution of an image,and they can preserve the texture and detail information.