A method for the recovery of JPEG compressed image sequences is proposed in this paper. The method is based on the reduction of compression artifacts, and it is inspired with the thoughts of super-resolution reconstruction. To minimize the quantization errors and restore the discrete cosine transformation components, the method utilizes the theory of Projection Onto Convex Sets (POCS) and Iterative Back Projection (IBP) algorithm, which helps computing the projections. It also applies Maximum A Posteriori (MAP) estimation techniques to remove Gaussian noise without damaging edges or details of the image. Experimental results show that the proposed method produces good Peak Signal to Noise Ratio (PSNR) results, and could not only remove blocking and ringing artifacts, but also recover details of images, especially in low bit-rate conditions.
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