Title: 3D reconstruction of UAV remote sensing sequence image based on iterative constraint weighting

Authors: Tiebo Sun; Meng Li; Weibing Wang; Chunyue Liu

Addresses: Department of Mechanical and Electrical Engineering, Jiangsu Food and Pharmaceutical Science College, Huai'an City, Jiangsu Province, 223003, China; School of Technology, Beijing Forestry University, Beijing 100083, China ' Department of Mechanical and Electrical Engineering, Jiangsu Food and Pharmaceutical Science College, Huai'an City, Jiangsu Province, 223003, China ' Department of Mechanical and Electrical Engineering, Jiangsu Food and Pharmaceutical Science College, Huai'an City, Jiangsu Province, 223003, China ' College of Automotive Engineering, Huaian Vocational College of Information Technology, Huai'an City, Jiangsu Province, 223003, China

Abstract: Aiming at the problem that the traditional 3D reconstruction method of UAV remote sensing sequence images takes time and affects the reconstruction accuracy, a 3D reconstruction method of UAV remote sensing sequence images based on iterative constraint weighting is proposed. Construct a UAV remote sensing platform, and process the images of UAV remote sensing sequences through image enhancement, uniform light processing and stitching. An iterative constraint weighting method is introduced to solve the global rotation matrix problem as a rotation vector in algebra. Through the iterative constraint weighting method, the second programming obtains the optimal solution of the global position and optimises the global position and attitude. According to the position and attitude parameters of the acquired UAV remote sensing sequence image and the reconstruction point cloud, the 3D reconstruction of the image is realised. Experimental results show that the method is short, accurate, effective and reliable.

Keywords: iterative constraint weighting; remote sensing sequence image; 3D reconstruction.

DOI: 10.1504/IJICT.2021.118574

International Journal of Information and Communication Technology, 2021 Vol.19 No.4, pp.371 - 390

Received: 13 Mar 2020
Accepted: 11 May 2020
Published online: 29 Oct 2021 *

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