Local PatchMatch Based on Superpixel Cut for Efficient High-resolution Stereo Matching
Xianjing Cheng, Yong Jun Zhao, S. P. Raja, Zhijun Hu, Xiaomin Yu, Wenbang Yang · Brazilian Archives of Biology and Technology · 2022
HIGHLIGHTS A new method of extracting the feature points in superpixels is proposed to compute the candidate disparities using non-local cost aggregation. A novel two-stage optimization framework for superpixel proposals by first getting the labels of feature points quickly and then consists the candidate label sets for updating the labels of pixels within the corresponding superpixel instead of assigning a label randomly to those pixels. The weight combination of intensity, gradient and binary image is designed for constructing an optimal minimum spanning tree to compute the aggregated matching cost.