Evaluation of dynamic programming among the existing stereo matching algorithms

There are various types of existing stereo matching algorithms on image processing which applied on stereo vision images to get better results of disparity depth map. One of them is the dynamic programming method. On this research is to perform an evaluation on the performance between the dynamic programming with other existing method as comparison. The algorithm used on the dynamic programming is the global optimization which provides better process on stereo images like its accuracy and its computational efficiency compared to other existing stereo matching algorithms. The dynamic programming algorithm used on this research is the current method as its disparity estimates at a particular pixel and all the other pixels unlike the old methods which with scanline based of dynamic programming. There will be details on every existing methods presented on this paper with the comparison between the dynamic programming and the existing methods. This can propose the dynamic programming method to be used on many applications in image processing

Efficient and accurate subpixel path based stereo matching

This paper presents an efficient algorithm to achieve accurate subpixel matchings for calculating correspondences between stereo images based on a path-based matching algorithm. Compared to point-by-point stereo matching algorithms, path-based algorithms resolve local ambiguities by maximizing the cross correlation (or other measurements) along a path, which can be implemented efficiently using dynamic programming. An effect of the global matching criterion is that the cross correlation at all pixels can contribute to the criterion; since cross correlation can change significantly even with subpixel changes, to achieve subpixel accuracy, it is no longer sufficient to first find the path that maximizes the criterion and then refine to subpixel accuracy. In this paper, by writing bilinear interpolation using integral images, we show that cross correlations at all subpixel locations can be computed efficiently and thus lead to a subpixel accuracy path based matching algorithm. Our results show the feasibility of the method and illustrate the significant improvements over the original path-based matching method. 1