With theoretical supports of kernel matching search method and Optimization approach (Gradient) are proposed our SR framework learns and selects the optimal Kernel ridge regression model when producing an SR image, which results in the minimum SR reconstruction error. We evalua...
The mapping function between low-resolution (LR) and high-resolution (HR) images is learned by using the method of regularized regression. Then, finding the optimal sparse subset of the training data set by kernel matching pursuit (KMP). The results show that this method can recover detailed ...