Parallel Belief Propagation Algorithm Conjugating Gradient and Intensity

Stereo matching is critical technology in vision measurement.MRF models are established to do with stereo problem.A parallel multi-scale belief propagation algorithm is used for MRF energy minimization and generating disparity map.Parallel algorithm is implemented based on traditional sequential algorithm with CUDA technology.In energy function,data term is conjugated with Gradient and intensity of images,smooth term is measured with the absolute difference of disparities between two adjacent pixels.With standard Middlebury stereo data sets as input,experiments show that the proposed algorithm has good real-time performance,running time is much less than the traditional sequential algorithm and the generated disparity map is excellent.