Abstract
Abstract. The stereo matching algorithm is commonly used in dealing with disparity discontinuous areas. However, the algorithm may have higher computational complexity and lack of well-aligned input images. To improve that, this paper presents an improved energy segmentation based stereo matching algorithm. The proposed algorithm incorporates gradient information of each segmented region into the energy function according to the facts that gradients inside the same segmentation should be closer than those from different segmentation. The invalid matching pixels are interpolated with vertical-horizontal nearest neighboring pixels to keep the consistency of stereo image pairs in the initial disparity map. Thus, the proposed method can reduce the deviations and the number of executions of the Random Sample Consensus (RANSAC) which arises from misalignment of input image pairs. Experiments results demonstrate that the proposed algorithm has a better disparity result while the running time is decreased by about 20%.
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