Abstract
Reflective tomography Lidar has been proved to be a new Lidar system with long distance and high resolution. The reflective tomography Lidar image is prone to clutter and artifacts; thus, it is important for space target recognition to extract the target from the image. In this study, we proposed image fusion algorithm combined with visual saliency could be applied to the target extraction of reflective tomography Lidar image, which can not only preserve the target information but also eliminate the clutter and artifacts in the image. The efficiency of this algorithm is shown by simulation and the experiment of the reflective tomography Lidar system. Also, we analyzed the main source of reflective tomography Lidar image artifacts and the reason why this algorithm could remove clutter and artifacts.
Highlights
Aerial and space target detection and identification have gained wide attention with the rapid development of aerospace science and technology
We proposed an image fusion algorithm combined with visual saliency, could use visual saliency detection to locate the target area, filter the effects of clutter and artifacts in the image, and generate the saliency map
In order to verify the effectiveness of this algorithm, the reflective waveform simulation system of the reflective tomography Lidar is established, which is combined with reflective tomography Lidar. 3DS Max is used to generate a 1 : 1 3D model of the detection target aircraft, in which the wingspan of the aircraft is about 13 meters, the length is about 19 meters, and the fuselage height is about 2.8 meters. e distance between the Lidar and the target coordinated origin is set at about 10 km, the elevation angle of the laser beam center relative to the target scene is set at 0 degrees, and the divergence angle of the laser beam is set at 1 mrad
Summary
Aerial and space target detection and identification have gained wide attention with the rapid development of aerospace science and technology. 2010, Murray et al [13] from Aretecompany combined the reflective tomography Lidar with range compressed and realized the imaging accuracy of 0.15 m for the non-cooperative target with a size of 1m at a distance of 22.4 km, which further improved the imaging resolution of the reflective tomography Lidar It is important for space target recognition to extract the target from reflective tomography Lidar image on account of the process of image reconstruction and is easy to produce clutter and artifacts. Sr,φ ∩ B where Sr,φ is a plane perpendicular to the direction of light, f(x, y, z) is the reflectance distribution of the target, and B is the set of points of the 3D target surface
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