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Image super-resolution using the specialized interior-point method

Using sparse representation for image super-resolution (SR) has been a hot topic in image processing recently. Many of them use the standard interior-point method to solve the l1-minimization problems which is essential in sparse representation. In this paper, we present a specialized interior-point method to do the image SR by using Preconditioned Conjugate Gradient (PCG) to compute the search step, and get the state-of-the-art results both qualitatively and quantitatively. The results showed that our method can achieve higher PSNR than conventional ones.