Multiple Kernel Regression Based Image Resolution for JPEG Images

Recently Learning –Based Approach for Super– resolution (SR) has been used witch generate favorable result. In this paper image super –resolution based on the multiple kernel regression is presented. This approach’s core is to learn the map between the space of high resolution image patches and the space of blurred high – resolution image patches.That are the interpolation result generated from corresponding low-resolution image. The superresolution image reconstruction can be transformed to solve linear equations whose size depends on the number of the training data. When the amount of the training data is large, it is time-consuming to solve the regression problem. To solve this problem select part of pairwise patches from training database instead of all the training data. In this method use Support Vector Regression(SVR) to generalize unseen data and unknown function. The experimental result show that it achieve three time better quality of image than other.