Efficient message reduction algorithm for stereo matching using belief propagation
Belief propagation (BP) is a popular global optimization technique in computer vision. However, it requires huge bandwidth and memory in hardware implementation because it iteratively processes messages between the neighboring nodes. In this paper, we propose an efficient message reduction algorithm that greatly reduces the bandwidth and memory consumption. Compared with the original message passing operation, we successfully reduce the memory and bandwidth with similar quality. For stereo matching of a VGA input where the disparity range is 64, the proposed algorithm can achieve 93.75% message memory reduction with about only 0.2–2.2% bad pixels quality degradation. The proposed algorithm greatly reduces the memory requirement and is suitable both for hardware and software realization.