An Improved Filtering for Fast Stereo Matching

Abstract

This paper presents a novel full-image guided filtering based on eight-connected weight propagation for dense stereo matching. The proposed method has three main features: first, the proposed eight-connected weight propagation is more approximate compared to previous approach, second, the pixels employed into the filtering are all the pixels without constrained by one fixed window, last but not least, computational complexity of each pixel at each disparity level is 0(1), and the implementation of the filter can efficiently parallelized on hardware platform. Performance evaluation on Middlebury data sets shows that the proposed method is one of the best local algorithms in terms of both accuracy and speed.