Improved hybrid method for image super‐resolution
Weiwei Xing, Yahui Zhao, Ergude Bao · IET Computer Vision · 2016
Improving image resolution has broad applications and is an important research topic. Recently, a hybrid method Adaptive Sparse Domain Selection (ASDS) combining a reconstruction‐based method and an example‐based method has been proposed to take advantage of the two, but may not reconstruct sufficient details. In this study, the authors propose to improve ASDS: Zeyde's method is first used to obtain an intermediate image with high‐frequency details, and then the obtained image is used to replace the autoregressive model of ASDS as the example‐based term. In addition, the authors may split the input image into patches and use different parameter settings for the patches of different amount of details. Experimental results demonstrate the improved hybrid methods can produce high‐quality images quantitatively and perceptually.