Color Image Super-Resolution Reconstruction Based on Sparse Representation

Abstract

This paper proposes a YUV color image super-resolution reconstruction algorithm based on sparse representation. The R, G, B components of color image are highly correlated, three-channel super-resolution independent reconstruction will lead to color distortion, so in this paper the color image is firstly converted to the Y, U, V three channels, and then super-resolution reconstruction. For choosing the regularization parameter, this paper proposes an adaptive regularization parameter method; it has a good inhibitory effect on image noise and adaptive super-resolution reconstruction of color images. The results of experiment show that the proposed algorithm has a better PSNR, compared with bicubic interpolation method and sparse representation. The adaptive super-resolution reconstruction can further improve the quality of the reconstructed image and the method is robust to image noise.