A modified area based local stereo correspondence algorithm for occlusions

Area based local stereo correspondence algorithms that use the simple 'winner takes all' (WTA) method in the optimization step perform poorly near object boundaries particularly in occluded regions. In this paper, we present a new modified area based local algorithm that goes some way towards addressing this controversial issue. This approach utilizes an efficient strategy by adding the concept of a computation skip threshold (CST) to area based local algorithms in order to add the horizontal smoothness assumption to the local algorithms. It shows similar effects to Dynamic Programming(DP) and Scanline Optimization(SO) with significant improvements in occlusions from existing local algorithms. This is achieved by assigning the same disparity value of the previous neighboring point to coherent occluded points. Experiments were carried out comparing the new algorithm to existing algorithms using the standard stereo image pairs and our own images generated by a Scanning Electron Microscope (SEM). The results show that the horizontal graphical performance improves similarly to DP particularly in occlusions but the computational speed is faster than existing local algorithms, due to skipping unnecessary computations for many points in the WTA step.