Restoration of compressed video using temporal information
Mark A. Robertson, Robert L. Stevenson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
This paper proposes a Bayesian method for the restoration of video sequences compressed using the discrete cosine transform (DCT). Two elements, both part of the Bayesian observation model, distinguish the proposed algorithm from the majority of other methods in the literature. The proposed algorithm incorporates temporal information from nearby frames -- past, present and future -- when forming an estimate of the current frame. Furthermore, this work uses a spatially-varying noise model to account for the noise introduced by quantization of the DCT coefficients. These two aspects of the observation model are used in conjunction with a Huber-Markov Random Field (HMRF) model to form a Bayesian estimate of each frame in the compressed video sequence.