Rateprediction structure complexity analysis for multiview video coding using hybrid genetic algorithms Efficient exploitation of the temporal and interview correlation is critical to multiview video coding (MVC), and the key to it relies on the design of prediction chain structure according to the various pattern of correlations. In this paper, we propose a novel prediction structure model to design optimal MVC coding schemes along with tradeoff analysis in depth between compression efficiency and prediction structure complexity for certain standard functionalities. Focusing on the representation of the entire set of possible chain structures rather than certain typical ones, the proposed model can given efficient MVC schemes that adaptively vary with the requirements of structure complexity and video source characteristics (the number of views, the degrees of temporal and interview correlations). To handle large scale problem in model optimization, we deploy a hybrid genetic algorithm which yields satisfactory results shown in the simulations.

Adaptive filtering for crossview prediction in multiview video coding We consider the problem of coding multiview video that exhibits mismatches in frames from different views. Such mismatches could be caused by heterogeneous cameras andor different shooting positions of the cameras. In particular, we consider focus mismatches across views, i.e., such that different portions of a video frame can undergo different blurrinesssharpness changes with respect to the corresponding areas in frames from the other views. We propose an adaptive filtering approach for crossview prediction in multiview video coding. The disparity fields are exploited as an estimation of scene depth. An Expectationmaximization (EM) algorithm is applied to classify the disparity vectors into groups. Based on the classification result, a video frame is partitioned into regions with different scenedepth levels. Finally, for each scenedepth level, a twodimensional filter is designed to minimize the average residual energy of crossview prediction for all blocks in the class. The resulting filters are applied to the reference frames to generate better matches for crossview prediction. Simulation results show that, when encoding across views, the proposed method achieves up to 0.8dB gain over current H.264 video coding.