Progressive adaptive correlation estimation(PACE) for WZVC

Wyner-Ziv video coding is a new paradigm for video compression, in which the prediction frames are possibly only available at the decoder. It exploits the redundancy between the source frame and the prediction frame at the decoder by utilizing their correlation information. However, such correlation information is difficult to estimate due to the absence of the prediction frame at the encoder and the lack of the source frame at the decoder. In this paper, we focus on this issue and propose a progressive adaptive correlation estimation (PACE) approach, in which the correlation information is progressively learned during the decoding process. Compared with our previous TRACE approach, PACE has similar performance in estimation accuracy as well as rate-distortion. Furthermore, it can be potentially integrated into more extensive WZVC applications, such as scalable applications and error-resilience applications.