Satellite imaging reconnaissance and aerial video surveillance may be the most important means for monitoring objects on the ground. First, we discuss the requirements on reconnaissance information for different missions including strategic operations, tactical tasks and fire control. In terms of precision and timeliness, we analyze the characteristics of reconnaissance images or videos captured by different platforms such as satellites and aerial vehicles. Then, we propose a general framework for tactical exploitation of multi-source images, which can provide a Common Operational Picture (COP) which is both real-time and precise enough for tactical purposes or even for fire control. According to this framework, we detect, identify, and track objects, and obtain higher precision by integrating the aerial videos and the satellite images. To show how to integrate the aerial videos and the satellite images, we study image registration techniques, analyze the differences between these two kinds of images, and present a feature-based geo-registration procedure. By spatially aligning these images, we can obtain the geographical coordinates of high precision in real time. The framework can be adopted for striking time-sensitive ground targets.
In the last decades, the world has been confronted with increasingly severe threats caused by small drones, especially for security of important places such as military bases and crucial activities in public areas. In comparison with traditional projectile weapons, high-energy laser weapons are especially suitable for countering such threats due to its precise and scalable effect with extremely low collateral damage. This paper presents a systematic design method of anti-drone laser weapons. First, this paper analyzes the system’s requirements. Secondly, describes the damage capability of high-energy laser weapons, presents how to determine the main parameters of the laser weapon system. Finally, for maneuverable deployment, this paper discusses the power supply for laser and cooling equipment, and shows how to reduce the power supply requirement and the system mass.
Airborne surveillance and reconnaissance play an increasingly crucial role in military operations. Aerial video can perceive dynamic events, track active targets and provide the real-time location of targets, but the poor accuracy of geographical coordinates limits its usefulness. Registration of aerial video to geo-referenced images is an effective means to improve the location accuracy. Generally, the aerial video and the geo-referenced images to be registered were taken at different times, from different viewpoints and by different cameras. Due to these differences, registration of aerial video to geo-referenced images is a challenging task. This paper discusses the essential issues of the problem, analyzes the characteristics of the images, and shows what features work better. Then, this paper presents a two-stage image registration algorithm, which is based on decomposition of transformation space. The first stage estimates the rotation parameter by matching histograms of weighted edge orientation between aerial image and geo-referenced image. The second stage determines the translation parameters by comparing partial images using partial Hausdorff distance. This approach is computationally efficient and robust to significant differences between the images to be aligned. Experiments have been conducted on real-world data, and the results have shown the good performance of the algorithm.
The world is confronted with increasingly severe challenges of unconventional threats with the popularization of small UAVs in civil fields. Due to the advantages such as killing or disabling targets with no or minimal collateral damage, the high energy laser weapon becomes one of effective means for coping with these kinds of threats. In order to guarantee cost-effectiveness, this paper presents an effect-based method for designing high energy laser weapons. First, we introduce the system components, the operating mechanism, and the damage capability of system. Second, we present the relationship equations between the on-target irradiance and all the influence factors. Finally, we discuss the laser selection problem and beam combining methods and show how to determine main technical parameters of the laser weapon system.
Edges play an important role in most computer vision and image analysis systems, and extracting structural edges is the
main goal of edge detection for many applications. But due to the presence of noise and texture, structural edge detection
is not a trivial work. In this paper, an approach is presented for structural edge detection, which is formulated as a
statistical pattern recognition problem in wavelet transform domain. In the approach, both inter-scale and intra-scale
dependences among wavelet coefficients are utilized, where the former dependences are encoded by inter-scale
coefficient ratios and the latter by anisotropic MRF model. To reduce the computational complexity, independent
mixture of Gaussian is used to model wavelet coefficients, which corresponds to Rayleigh distribution for gradient
magnitude, and posterior probabilities are computed to measure the edge strengths. Inter- and intra-scale dependences
among coefficients are utilized to suppress noise and texture, and these measures can significantly improve edge
continuity in scale space. To show the effectiveness of the presented algorithm, experiments are conducted on various
kinds of real-world images, and several results are given for assessment.
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