Optimized inpainting-based macroblock prediction in video compression

In this paper, we propose an optimized inpainting-based macroblock prediction mode in the state-of-the-art H.264/AVC video engine. Parallel with the existing intra- and inter- modes, it is regularized by the global tempo-spatial consistency between the current MB and the co-located decoded region. The target is formulated as a local optimization problem by minimizing the energy of Markov Random Field (MRF). An ordered belief propagation (BP) is developed to solve the optimization problem with spatio-temporal consistency regularity and achieve the patch assignment of largest probability. It ensures a stable marginal belief distribution through updating local messages via iterative forward and backward process, to impose a prioritized inference on the structure. Rate-distortion optimization is used to evaluate the mode selection within the inpainting-based prediction mode, intra- and inter modes. It has been implemented into H.264/AVC, and achieves bit-rate saving and higher PSNR performance, especially in low bit-rate.