The airborne video streams of small-UAVs are commonly plagued with distractive jittery and shaking motions, disorienting rotations, noisy and distorted images and other unwanted movements. These problems collectively make it very difficult for observers to obtain useful information from the video. Due to the small payload of small-UAVs, it is a priority to improve the image quality by means of electronic image stabilization. But when small-UAV makes a turn, affected by the flight characteristics of it, the video is easy to become oblique. This brings a lot of difficulties to electronic image stabilization technology. Homography model performed well in the oblique image motion estimation, while bringing great challenges to intentional motion estimation. Therefore, in this paper, we focus on solve the problem of the video stabilized when small-UAVs banking and turning. We attend to the small-UAVs fly along with an arc of a fixed turning radius. For this reason, after a series of experimental analysis on the flight characteristics and the path how small-UAVs turned, we presented a new method to estimate the intentional motion in which the path of the frame center was used to fit the video moving track. Meanwhile, the image sequences dynamic mosaic was done to make up for the limited field of view. At last, the proposed algorithm was carried out and validated by actual airborne videos. The results show that the proposed method is effective to stabilize the oblique video of small-UAVs.
As a new type of aviation remote sensing earth observation system, the UAVRSS (Unmanned Aerial Vehicle remote sensing system) is used in civil remote sensing field more and more. In order to improve the efficiency of the remote sensing image processing and making the Orthophoto of the UAVRSS, in this paper one method is presented to improve the precision of the Orthophoto without the Ground Control Point(GCP) and the high precision sensors, such as the POS and the IMU. Through some real flying experiments of the UAVRSS, the data and the images were obtained. These data and the images were analyzed by the method. The result shows that the precision of the Orthophoto.
Due to the affection of large moving object in the video image, the ordinary image stabilization algorithms can't get
precise motion vector of the image. In this paper, a new image stabilization method that explicitly deals with video
images containing large moving object is given out. It detects a rough area containing moving object first. Then this area
will be got rid of from source image. Finally, a feature area taken from the rest part is used to calculate the image motion.
For the affection of moving object has been eliminated, motion vector's precision of the image is improved greatly.
With maturation of UAV (Unmanned Aerial Vehicle) key techniques, the UAV aviation is more stable than before. That
shows us the possibility of reconnaissance in atrocious environment. Here the structure of an UAV remote sensing
platform is given out first. Then the control system modules of aerial remote sensing and their functions with each
realization are discussed in detail. The experiments show that the system can satisfy the needs for aerial remote sensing