Abstract—In blocking-matching algorithms, a local window is used to measure the similarity (or dissimilarity) between pixels of a stereo pair. Although some area-based stereo matching methods have been developed and work well in many types of regions, such as textureless or object boundary regions, there are still cases where these methods are weak. In this paper, we propose an enhanced blocking-matching method to solve the correspondence problem in stereo matching. The proposed algorithm is an improved adaptive support weight method, which first classifies the pixels in the reference image and then uses the spatial weight variable window method and adaptive support weight method for each type of pixel. We also analyze and show the advantages and disadvantages of the variable window method and the adaptive support weight method and suggest solutions for cases where the two methods may not be ideal. The experimental results using the Middlebury images show that the proposed method outperform local stereo methods.

Index Terms—Stereo matching, spatial weight, adaptive window.

The authors are with the Computer Engineering Department, Sungkyunkwan University, Suwon, Republic of Korea (e-mail: {hongphuc, cwan}@skku.edu).

 

Cite:Phuc Nguyen Hong and Chang Wook Ahn, "Stereo Matching Using Fusion of Spatial Weight Variable Window and Adaptive Support Weight," International Journal of Computer and Electrical Engineering vol. 6, no.3, pp. 211-217, 2014.