Image Super-Resolution Reconstruction based on Adaptive Secletion Regularization Parameter

In order to further improve the quality of reconstructed images, this paper proposed a regularization super-resolution reconstruction algorithm based on adaptive selection regularization parameter. We can get the information of different regions by image segmentation. In this paper, we use the image region information to select regularization parameters adaptively in image super-resolution regularization model, which can not only smooth the noise, but also can maintain the edge details of image. The experimental results show that the proposed method can select the regularization parameter adaptively, and get better reconstruction results.