An Intensity-Independent Stereo Registration Method of Push-Broom Hyperspectral Scanner and LiDAR on UAV Platforms

Unmanned aerial vehicles (UAVs) equipped with hyperspectral scanners and light detection and ranging (LiDAR) can flexibly acquire rich spectral and geometric information about the observation scene. To combine the complementary advantages of multisource data, the stereo registration of hyperspectral images and LiDAR data has become one of the hot topics in the remote sensing community. However, existing research works are more focused on exploiting intensity information from multisource data, which is applicable to data acquired on manned vehicle platforms or satellite platforms. For UAV platforms with poor stability and limited load, the low signal-to-noise ratio of LiDAR data and the complex distortion of push-broom images bring great challenges to stereo registration. Under this circumstance, an intensity-independent stereo registration method is proposed in this article, which is based on the physical model of the integrated system and the sensor detection principles. Specifically, the proposed method utilizes the position and orientation system (POS) to reduce the impact of UAV platform motion on hyperspectral imaging, and projection errors are eliminated by the ray tracing model with aid of LiDAR data. Finally, a virtual ray decomposition model based on geometric features is constructed to realize the stereo registration of hyperspectral images and LiDAR data. Compared with an advanced solution and professional processing software, the proposed method has shown better registration performance on two data of different scenarios.

Automated summary

This article proposes an intensity-independent stereo registration method for UAV platforms, which combines a physical model of the integrated system, sensor detection principles, position and orientation system, and ray tracing model to achieve stereo registration of hyperspectral images and LiDAR data. Experimental results show that the proposed method has better registration performance in different scenarios.