Abstract
In this paper, wp cast stereo matching as a problem in merit maximization. This is achieved by the formulation of a merit function which influence the similarity between primitives in the right and left images and the mutual dependency between primitives. Stereo matching are done by finding the "best" paths that maximize the merit function. This is handled by using dynamic programming technique. With this algorithm, a global optimum matching can be obtained. We give a mathematical description for the merit function and the algorithm has been implemented. The experimental results are presented to show the efficacy of the proposed stereo matching method.
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