A Proposal to Suppress the Training Stage in a Coset-Based Distributed Video Codec
Distributed video coding (DVC) is a coding paradigm that gives the decoder the task to exploit the source statistics to achieve efficient compression. Many approaches to the DVC problem have recently appeared in the literature, including the PRISM codec. Instead of encoding the deterministic quantized prediction error residual, PRISM partitions the quantization lattice into cosets and sends the index of the coset each quantized coefficient belongs to. Estimating the number of cosets is of crucial importance to achieve good coding efficiency. In PRISM, this is determined during an offline training phase. The present work aims at being a starting point for the suppression of the training stage of PRISM at the cost of sending the number of cosets for each DCT coefficient. The statistics of the number of cosets are analyzed to figure out the maximum compression efficiency achievable by entropy coding. Furthermore the paper discusses some techniques that might be used to lower the amount of transmitted bits. Based on these results, directions for future works are proposed