Abstract:

Singleframe super resolution (SR) image reconstruction algorithms based on maximum a posteriori (MAP) have preferable reconstruction results and noise robustness but high time and space complexity. To improve efficiency of template convolutionbased MAP (TCMAP) algorithm and decrease its memory consumption, a new imagecontentbased adaptive block TCMAP algorithm is proposed. Optimal size of image block is studied, and according to average gradients of image blocks, several blocks in smooth areas are combined to reduce the influence on block boundary effects, further block boundary extension is used to suppress block effects. Experiments show that both run time and memory consumption of TCMAP algorithms are decreased, while the quality of reconstructed images makes little difference.