Optimal reference view selection algorithm for low complexity disparity estimation

Multi-view video coding (MVC) is composed of multiple video sequences captured simultaneously by multiple closely spaced cameras. Such a system demands a higher computational complexity due to the increased number of cameras. Disparity estimation (DE) is one of the compression techniques used to remove inter-view redundancy in MVC, which causes high complexity. In order to overcome the problem of high computational complexity in real-time MVC, an optimal reference view selection algorithm is proposed. The proposed scheme decreases the coding complexity by reducing one-directional DE operation and minimizing the decrease in coding performance in MVC.