Target location is a fundamental application in aerial image process. In this work, a fast normalized cross correlation algorithm is proposed for the application of target location in aerial image. Firstly, normalized cross correlation has been proved equivalent to Euclidean distance. In the search step, the target template and the corresponding window of base image are projected to a set of mutually orthonormal vectors for calculating the lower bound of the distance, where the windows with too large distance relative to the target template will be rejected in this step. Finally, the directly normalized cross correlation calculating is applied to the rest windows of base image to achieve the final correct location of target. The experimental results show that compared with traditional method, the proposed method significantly improved the computational complexity without sacrificing the spatial resolution or the accuracy of the match result.
KEYWORDS: Target detection, Detection and tracking algorithms, Signal to noise ratio, Stars, Point spread functions, Aerospace engineering, Image processing, Space reconnaissance, Nonlinear filtering, Infrared detectors
In this paper, aiming at the small target detection problem in the infrared image sequence, we propose a small target detection method based on maximum likelihood estimation and NNLoG spot detection operator. Compared with the traditional method, our proposed method can partially solve the nonlinear motion of the small target in image sequence. The real target trajectory is approximated by polynomial to enhance the signal to noise ratio of target. To validate the proposed method, we create eight experiments to simulate. The experiment result shows that our method is very valuable for small target detection.
Video stabilization is a critical step for improving the quality of videos captured by unmanned aerial vehicles. However, the complicated scenarios in the video and the need for instantaneously presenting a stabilized image posed significant challenges to the existing methods. In this work, an instantaneous video stabilization method for unmanned aerial vehicles is proposed. This new approach serves several purposes: smoothing the video motion in both two-dimensional and three-dimensional (3-D) scenes, decreasing the lags in response, and instantaneously providing the stabilized image to users. For each input frame, our approach regenerates four short motion trajectories by applying interframe transformations to the four corners of the image rectangle. An adaptive filter is then performed to smooth motion trajectories and suppress the lags in response simultaneously. Finally, at the stage of image composition, the quality of image is considered for selecting a visually plausible stabilized video. Experiments show that our approach can stabilize various videos without the need for user interaction or costly 3-D reconstruction, and it works as an instant-process for videos from an online source.
The high portability of small Unmanned Aircraft Vehicles (UAVs) makes them play an important
role in surveillance and reconnaissance tasks, so the military and civilian desires for UAVs are
constantly growing. Recently, we have developed a real-time video exploitation system for our small
UAV which is mainly used in forest patrol tasks. Our system consists of six key models, including
image contrast enhancement, video stabilization, mosaicing, salient target indication, moving target
indication, and display of the footprint and flight path on map. Extensive testing on the system has
been implemented and the result shows our system performed well.
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