_applied sciences_  
_Article_  
Mosaicing Technology for Airborne Wide Field-of-View  
Infrared Image. _Appl. Sci._**2023**, _13_, 8977. [[https://doi.org/10.3390/app13158977](https://doi.org/10.3390/app13158977)]([https://doi.org/10.3390/app13158977](https://doi.org/10.3390/app13158977))  
**Colographic**: 0 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))). **Critical**: 0 2023 by the authors. Licensee MDPI, Basel, Switzerland. Multi-detector parallel scanning is a panoramic camera that originated from the traditional film era, which has a large lateral field of view. Combined with the application of CCD (Charge Coupled Device) technology, the multi-detector parallel scanning camera uses a linear CCD parallel to the flight direction on the focal plane of the objective lens instead of the slot imaging and scans along with the objective lens perpendicular to the flight direction to obtain an image. Because of the wide swing of the objective lens, it can image a wide range of areas on both sides of the route, which is a wide-field aerial scanning image. The scanning field of view of a multi-detector parallel scanning camera can be designed as very large, and wide images can be acquired only by a linear detector, which greatly improves the image acquisition efficiency and is often used for fast acquisition of infrared/night vision images. However, because the focal length of the multi-detector parallel scanning camera is fixed and the object distance increases with the increase of scanning angle, the scale on both sides of the image will gradually shrink, and the whole image will produce so-called panoramic geometric distortion. In addition, while scanning, the airplane moves forward, and the nonlinear factors of scanning mirror swing make the geometric distortion of the image more complicated. In order to acquire images of a certain area, the multi-detector parallel scanning camera is often used to acquire the images through the left and right swing of the objective lens during flight, and the adjacent images are designed to be overlapped according to the flight path, and then the regional images are obtained by image processing. However, due to many interference factors during flight, the overlap between the acquired images is constantly changing, which increases the complexity and difficulty of regional image processing. At present, there are few reports on the research about the automatic mosaic processing of wide-field aerial scanning images, but more research is on the mosaic of CCD images and other aerial area array images acquired by UAV (unmanned aerial vehicle). [PERSON] et al. proposed using SIFT algorithm to detect candidate feature points and combining the longitude and latitude coordinates of UAV array image and the location relationship of overlapping areas to conduct rough matching of feature points, using the random sampling consensus algorithm to solve the projection transformation matrix to complete the concatenation of two adjacent farland remote sensing images and designed a pyramid stitching strategy to complete the stitching of 128 high-resolution array images [1]. [PERSON] et al. proposed an improved SPHP (Shape Preserving Half Projection) algorithm to solve the problem of deformation or ghosting in UAV remote sensing array stitching images that were easily affected by geomorphic factors [2]. [PERSON] introduced a feature point matching algorithm to design a new UAV remote sensing image fast stitching system to address the issues of long matching time and slow stitching speed in the currently designed UAV array remote sensing image stitching system [3]. [PERSON] et al.