An improved side information generation for distributed video coding

This paper presents a side information (SI) scheme for distributed video coding based on multilayer perceptron. The suggested scheme predicts a Wyner–Ziv (WZ) frame from two decoded key frames. The network is trained offline using patterns from different standard video sequences with varied motion characteristics to achieve generalization. The proposed scheme is simulated along with other standard video coding schemes. Performance comparisons have been made with respect to training convergence, rate distortion (RD), peak signal to noise ratio (PSNR), number of requests per SI frame, decoding time requirement, etc. In general, it is observed that the proposed scheme has a superior SI frame generation capability as compared to its competent schemes.