Iterative Multiview Side Information for Enhanced Reconstruction in Distributed Video Coding
Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW) and Wyner and Ziv (WZ). DVC entails low complexity encoders as well as separate encoding of correlated video sources. This is particularly attractive for multiview camera systems in video surveillance and camera sensor network applications, where low complexity is required at the encoder. In addition, the separate encoding of the sources implies no communication between the cameras in a practical scenario. This is an advantage since communication is time and power consuming and requires complex networking. In this work, different inter-camera prediction techniques for Side Information (SI) generation are explored and compared in terms of prediction quality, complexity and Rate Distortion (RD) performance. Further, a technique called Iterative Multiview Side Information (IMSI) is introduced, where the final SI is used in an iterative reconstruction process. The simulation results show that IMSI significantly improves the RD performance for video with significant motion and activity. Furthermore, DVC outperforms AVC/H.264 Intra for video with average and low motion but it is still inferior to the Inter No Motion and Inter Motion modes.