Research on UAV remote sensing image matching using feature combination detection algorithm

doi:10.13474/j.cnki.11-2246.2019.0006

Abstract

Abstract: Image matching is fundamental to remote sensing image mosaic and 3D modeling using UAV remote sensing images.A fast matching method of UAV images based on feature combination and RANSAC algorithm is proposed in this paper.The matching method first uses the AKAZE algorithm to detect the feature points of the image,and then uses the SIFT descriptor to describe the feature vectors and obtain the main direction of these feature points.Finally,the accurate matching is made by the RANSAC algorithm based on the single mapping transformation matrix.In this paper,the writer has carried out the experimental comparison analysis on the proposed matching method and algorithms. And the results were shown as follows:the matching method proposed in this paper inherits the fast matching ability of the AKAZE algorithm,with a total matching time in the middle of that consumed by the AKAZE algorithm and the SIFT algorithm,which accounts for around 20% of the time needed using the BRISK algorithm.At the same time,this matching method inherits the performance of multiple matching points of the SIFT algorithm.From the overall matching effect,the matching method in this paper is superior to the AKAZE,SIFT and BRISK algorithms.

Key words: image matching, feature combination detection algorithm, RANSAC algorithm, UAV image

CLC Number:

P237

WANG Xiaohong, HE Zhiwei, DENG Shixiong, CAO Liuxia, LI Chuang. Research on UAV remote sensing image matching using feature combination detection algorithm[J]. 测绘通报, 2019, 0(1): 29-33.

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