A novel non-parametric transform stereo matching method based on mutual relationship

To cope with the problem of the vast majority local stereo matching approaches that rely highly on the statistical characteristics of the image intensity, a novel non-parametric transform stereo matching method based on mutual relationship is proposed. The traditional non-parametric transform is investigated, and its limitations are analyzed. In order to take the pixels’ special location information into consideration during finding stereo correspondences, the original gray values of the neighborhood pixels whose relative position is one unit greater than that of the center pixel are replaced by the gray values interpolation of the four pixels surrounding it. Then the new non-parametric transform stereo matching is performed. The proposed approach is tested with both the standard image datasets and the images captured from realistic scenery. Experimental results are compared to those of intensity-based algorithms; the percentage of bad matching pixels is almost equivalent to the other examined algorithms, and the proposed algorithm exhibits robust behavior in realistic conditions.