332 / 1971-01-01 00:00:00

L1-l2 Hybrid Noise Model To Image Super-resolution

Hybrid noise model,Super-resolution,L1 norm,L2 norm,adaptive membership degree

Abstract—L1-L2 hybrid noise model (HNM) method is proposed in this paper for image/video super-resolution. This method has the advantages of both L1 norm minimization (i.e. edge preservation) and L2 norm minimization (i.e. smoothing characterization). In view of noise distribution changing and selecting L1 norm minimization or L2 norm minimization, we propose an efficient adaptive membership degree (AMD) method, which get the ideal result but the proposed AMD method can reduce the number of iterations and save much computational cost. Experimental results indicate that the proposed method is of higher peak signal to noise ratio (PSNR) and structural similarity (SSIM). And it has better reconstruction effect in edge and smoothing part.