Abstract
This study proposes a novel method for image registration and fusion via commonly used visible light and infrared integrated cameras mounted on medium-altitude unmanned aerial vehicles (UAVs).The innovation of image registration lies in three aspects. First, it reveals how complex perspective transformation can be converted to simple scale transformation and translation transformation between two sensor images under long-distance and parallel imaging conditions. Second, with the introduction of metadata, a scale calculation algorithm is designed according to spatial geometry, and a coarse translation estimation algorithm is presented based on coordinate transformation. Third, the problem of non-strictly aligned edges in precise translation estimation is solved via edge–distance field transformation. A searching algorithm based on particle swarm optimization is introduced to improve efficiency. Additionally, a new image fusion algorithm is designed based on a pulse coupled neural network and nonsubsampled contourlet transform to meet the special requirements of preserving color information, adding infrared brightness information, improving spatial resolution, and highlighting target areas for unmanned aerial vehicle (UAV) applications. A medium-altitude UAV is employed to collect datasets. The result is promising, especially in applications that involve other medium-altitude or high-altitude UAVs with similar system structures.
Highlights
This study aims to develop a method of visible and infrared image registration and fusion for medium-altitude unmanned aerial vehicles (UAVs) applications
We employ a medium-altitude UAV, which is used in earthquake emergency and rescue to collect images of disaster areas effectively and accurately with the aid of imaging devices rescue to collect images of disaster areas effectively and accurately with the aid of imaging devices
To adapt to the non-strictly aligned characteristics of edges, this study proposes a new registration method based on a Gaussian distance field
Summary
Medium-altitude unmanned aerial vehicles (UAVs) are an important information acquisition platform in the integrated Earth observation network [1]. UAVs offer the advantages of flexibility and rapid response. Compared with manned aerial vehicles, medium-altitude UAVs can work in high-risk areas to accomplish detection missions. They are capable of flying long distances and feature a wide detection range and an operation time that lasts longer than that of low-altitude
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