Distributed Video Coding (DVC) is a recently proposed paradigm in video communication, which fits well emerging applications such as wireless video surveillance, multimedia sensor networks, wireless PC camera, and mobile cameras phones. These applications require a low complexity encoding, while possibly affording a high complexity decoding. In DVC, a Side Information (SI) is estimated at the decoder, using the available decoded frames, and used for the decoding and reconstruction of other frames. In this PhD thesis, we propose new techniques in order to improve the quality of the SI. First, successive refinement of the SI is performed after each decoded DCT band. Then, a new scheme for SI generation based on backward, forward motion estimations, and Quad-tree refinement is proposed. Furthermore, new methods for combining global and local motion estimations are proposed, to further improve the SI, using the differences between the corresponding blocks and Support Vector Machine (SVM). In addition, algorithms are proposed to refine the fusion during the decoding process. Furthermore, the foreground objects are used in the combination of the global and local motion estimations, using elastic curves and foreground objects motion compensation. Extensive experiments have been conducted showing that important gains are obtained by the proposed techniques compared to the classical DISCOVER codec. In addition, the performance of DVC applying the proposed algorithms outperforms now the performance of H.264/AVC Intra and H.264/AVC No motion for tested sequences. Besides that, the gap with H.264/AVC in an Inter IB…IB configuration is significantly reduced.
