Abstract: To reduce the false match rate so as to increase Psnr and reduce computing complexity, a new algorithm for disparity estimation of the stereo image pair is proposed. Continuity and uniqueness constraints are employed to build up the Gaussian model for the computation of prior possibility, and the best matching block is determined according to maximum a posteriori (MAP) criterion. The angle of view constraint proposed in this paper and the ordering constraint, which are the pixels’ position range and sequence relation, are imposed to correct the Gaussian prior possibility calculation model which gives punishment to the candidate blocks that violate these two constraints. Constraints reduce the scanning range so that computing complexity and possibility of false matching are both reduced. Experimental results show that the proposed algorithm gives PSNR about 02~4.0 dB upgrade in contrast to the normalized correlation. In particular, images with more noise or bigger disparities will be given more upgrade. In addition, the disparity map obtained from the proposed algorithm has better smoothness than that from the normalized correlation.

Key words: disparity estimation, stereo image matching, stereo image coding