A real-time panoramic imaging system and equipment carried by a micro UAV

Abstract

A miniature drone-borne real-time panoramic imaging system, including real-time panoramic imaging equipment, wireless signal transmission and control board; The signal transmission and control board, the wireless signal transmission and the control board are connected with the wireless antenna; the optical protective cover is a transparent cylindrical cover, the reflector is a conical surface mirror, and the high-definition camera is placed at the optical focus formed by the conical surface mirror; the wireless The antenna is mounted on the outside of the housing. The micro UAV-borne real-time panoramic imaging system and equipment designed based on the present invention can obtain real-time large-scale scene images without image splicing. It has good real-time performance, simple structure, and low cost. Reality and other fields play an important role.

Description

technical field [0001] The invention relates to a real-time panoramic imaging system and equipment carried by a micro UAV. Background technique [0002] The UAV remote sensing system has many advantages such as small size, light weight, low cost, low loss, reusability, and low risk. Handle non-military areas such as emergencies. The high timeliness, high resolution and other performances of UAV remote sensing are unmatched by traditional satellite remote sensing, and are more and more favored by researchers and producers, greatly expanding the application range and user groups of remote sensing, and have a wide range of applications prospect. [0003] At present, the research on panoramic imaging technology at home and abroad mainly focuses on ground acquisition, and there are few studies on aerial panoramic image acquisition. To sum up, there are mainly two methods for obtaining panoramic imaging: image mosaic method and fisheye lens method. One of the panoramic imaging...

AI Technical Summary

Problems solved by technology

Although this method has high imaging resolution, the imaging speed is slow and the stitching algorithm is complicated. Generally, only cylindrical panoramic images can be stitched together, which does not meet the requirements of a single viewpoint, and the cost is high and the system is complex, which cannot meet the needs of real-time panoramic imaging.

In addition, there are still several problems in the mosaic images carried by drones: first, the inclination angle of the images is too large and irregular, the degree of course overlap is too small (less than 20%), and the gray scale is inconsistent, which makes image matching difficult. Low precision will cause adverse effects on subsequent processing; second, the small image size and large number of images will result in heavy workload and low efficiency, so it is necessary to study efficient and highly automated processing methods; third, the flight path is curved, and the image Irregular and too small side overlap (many are less than 10%), which brings difficulties to the extraction and layout of connection points and affects the accuracy of aerial triangulation

At the same time, since most UAV imaging platforms use non-measurement cameras, the imaging quality is poor, the image distortion is large, irregular, and the difference in radiation information is obvious. These unfavorable factors bring direct challenges to image stitching.

[0004] While obtaining a large field of view, the fisheye lens has its disadvantages, that is, it will produce serious barrel distortion, which is difficult to correct, and the imaging resolution is low

High-quality fisheye lenses usually use more than 10 elements and high-quality optical materials, so the system is complex and expensive

[0005] As mentioned above, in summary, the current UAV imaging technology has the following problems: the imaging speed is slow, the real-time performance is poor, and the complete panoramic image cannot be obtained at the same time, let alone the dynamic panoramic image, and the data volume of the acquired image is large, and the stitching algorithm is complicated. It also has the inability to meet the requirements of a single viewpoint, high cost, and complex system

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