Side information extraction based on motion trajectory learning for distributed video coding

Distributed video coding (DVC) is an emerging application of distributed source coding (DSC). Since coding complexity is shifted from encoder sides to decoder sides, DVC is appropriate and useful for the environments where low power encoding is allowed. The coding performance of DVC is greatly affected by side information extracted from bi-directional key frames which is enhanced through channel decoding. Therefore, efficient side information extraction methods have been considered to be an important subject for better coding performance of DVC. In this paper, we propose a method to effectively extract the side information for which motion-compensated frame interpolation is performed based on asymmetric 6-tap FIR filters in sub-pel motion estimation. For more precise motion estimation, motion trajectories are found through several consecutive key frames by linear regression. To avoid unreliable estimation on motion, a criterion function decides whether the extracted side information is effective or not. Experimental results show that the proposed side information extraction method achieves average 0.3dB in BDPSNR and maximum 0.85 dB improvements in coding gain compared to the DISCOVER codec.