Abstract
A multispectral imaging system often cannot capture 3D spatial information owing to hardware limitations,which diminishes the effectiveness across various domains.To address this problem,we have de-veloped a multispectral stereo imaging system along with an adaptive 3D reconstruction algorithm.Unlike existing unmanned aerial vehicle stereo imaging systems,our multispectral stereo imaging system uses two multispectral cameras with asymmetric spectral bands positioned at different angles.This design enables the acquisition of a higher number of bands and lateral spatial information while maintaining a lightweight struc-ture.This system introduces challenges such as large geometric distortions and intensity differences between multiple bands.To accurately recover 3D spatial information,we propose an adaptive 3D reconstruction method.This method employs a position and orientation system-assisted projection transformation and a normalized threshold adjustment strategy.Finally,mutual information is used to reconstruct the multispec-tral images densely,effectively addressing nonlinear differences and generating a comprehensive multispectral point cloud.Our stereo system was used for two real data collections in different regions,and the efficacy of the proposed 3D reconstruction method was validated by comparing it with existing methods and commercial software.
基金项目
National Science Fund for Outstanding Young Scholars(62025107)
Open Fund Project of KuiYuan Laboratory(KY202423)
维普
万方数据