AN adaptive L1-L2 hybrid error model to super-resolution
نویسندگان
چکیده
A hybrid error model with L1 and L2 norm minimization criteria is proposed in this paper for image/video super-resolution. A membership function is defined to adaptively control the tradeoff between the L1 and L2 norm terms. Therefore, the proposed hybrid model can have the advantages of both L1 norm minimization (i.e. edge preservation) and L2 norm minimization (i.e. smoothing noise). In addition, an effective convergence criterion is proposed, which is able to terminate the iterative L1 and L2 norm minimization process efficiently. Experimental results on images corrupted with various types of noises demonstrate the robustness of the proposed algorithm and its superiority to representative algorithms.
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