Sparse Matching and Dense Matching of UAV Epipolar Images

doi:10.13474/j.cnki.11-2246.2017.0150

Abstract

Abstract: Converting UAV images to epipolar images, makes a good effect on reducing the search space of corresponding point matching. On this basis, SIFT operator based sparse stereo matching and BP algorithm based dense stereo matching were presented in this paper. The result indicated that:Less corresponding points, simple calculation and accurate spatial coordinates were shown in the results of SIFT operator, so SIFT operator was suitable to acquire summary spatial information in a big-scale area. The computation of BP algorithm was complex but a large number of same points were outputted, which indicated that BP algorithm applied to 3D reconstruction in a small range. In a word, each of them has its own advantages and disadvantages, and they can be complementary.

Key words: SIFT operator, sparse stereo matching, BP algorithm, dense stereo matching

CLC Number:

P237

ZHANG Man, SHEN Shengyu, HU Teng. Sparse Matching and Dense Matching of UAV Epipolar Images[J]. 测绘通报, 2017, 0(5): 39-42,55.

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