Intra frame compression and video restoration based on conditional markov processes theory

Digital images and video have significant statistical redundancy due to high intra and inter-frame correlation. Modeling images and video using two-dimensional Markov processes with discrete states maximizes the use of images and video redundancy while processing. Intra-frame compression algorithm proposed below allows 2–3 times increase in processing speed for comparable compression ratios. Nonlinear filtering algorithm of video (distorted during transmission on a radio channel in terms of interference) allows effective video restoring even for negative signal/noise ratio unlike the known methods. A distinctive feature of this algorithm is ease of implementation with minimal computing resources.