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This work tackles the problem of side information generation for the case of large-duration GOPs in distributed video coding. Based on a previously developed technique for side-information enhancement, we develop a genetic algorithm particularly designed for large GOPs, taking into account the GOP size, the additional bitrate incurred by encoding hash information, as well as the decoding complexity. The proposed algorithm makes use of different interpolation methods available in the literature in a fusion-based approach. A significant gain in the average PSNR that can reach 2 dB is observed with respect to the best performing interpolation technique, while the algorithm is run for no more than 18% of the total number of blocks in a given video sequence. On the other hand, while the encoding complexity is a main concern in distributed video coding, the proposed solution incurs no additional complexity at the encoder side in the case of hash-based Wyner-Ziv video coding.

A GENETIC APPROACH FOR IMPROVING THE SIDE INFORMATION IN WYNER-ZIV VIDEO CODING WITH LONG DURATION GOP