Fast disparity estimation using spatio-temporal correlation of disparity field for multiview video coding

Abstract

Disparity estimation is adopted by multiview video coding (MVC) to reduce the inter-view redundancy. However, it consumes enormous computational load. In this paper, a fast disparity estimation is proposed by using the spatio-temporal correlation and the temporal variation of disparity field. For each macroblock, a temporal prediction of the disparity vector is calculated first by utilizing the smoothed disparity field of the previous coded frame. Then, the search center is selected among the candidates obtained from spatio-temporal neighboring disparity vectors, and deemed to be a preliminary disparity vector. Finally, the search range is predicted adaptively by using the distance between the search center and the temporal prediction of the disparity vector, and then the search is implemented in a limited range. The distance represents the temporal variation of the disparity vector. As compared to the full search algorithm in MVC reference software, experimental results show that an average 96% reduction of the computational complexity is achieved, while the rate-distortion performance remains the same. As compared to the fast search algorithm in MVC reference software, experimental results show that an average 43% reduction of the computational complexity is achieved, and the rate-distortion performance of the proposed algorithm has been improved.