In this paper, a super-resolution reconstruction algorithm based on Projection onto Convex Sets (POCS) and wavelets transform is proposed. A high resolution image, after wavelet transform, can be decomposed into two parts: approximate subband and detail subbands. Under some special conditions, the blurred low-resolution images can be thought as the wavelets transform approximate subbands of a high resolution image. Based on the above relationship, we can construct a series of convex sets and then apply the POCS method to recovering high resolution image based on the convex sets. After finite iterative computation, the desired high solution image can be obtained. The experimental results show that the algorithm has good performance in super-resolution reconstruction when the magnification is large enough.

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