A fast dictionary training algorithm for single image super-resolution

Abstract

Generally the dictionary for single image super-resolution is trained by iterations of MP algorithm and K-SVD algorithm. Using the dictionary, low resolution images can be restored to high resolution images with high quality. But the training process always takes a lot of time. So in this paper we use SVD to analyze the space relationship between the high and low resolution samples, and present a cluster based algorithm for dictionary training. Compared with the K-SVD based algorithm, the proposed algorithm trains the dictionary with a much higher speed, and restores the images with similar visual quality. © 2013 Springer-Verlag.