Infrared small target detection technology plays an extremely important role in military remote warning, satellite remote sensing technology, guidance and anti-mission, UAV detection and tracking, and other fields. Most traditional algorithms have high detection false alarm when there are thin and highlighted patterns in the background. To address the abovediscussed problem, this paper proposes an infrared small target detection algorithm based on multi-direction derivative and local contrast. The algorithm utilizes the two-dimensional Gaussian distribution of small targets to compute multidirectional derivative on each pixel of the image. Simultaneously, a sliding window is constructed to compute the local contrast. Finally, the derivative result and the local contrast is combined to get the target saliency map. Compared with traditional infrared small target detection algorithms in terms of background suppression factor (BSF) and signal-to-clutter ratio (SCR), our algorithms has better performance in both indicators. In addition, Receive Operating Characteristic (ROC) curve is introduced to evaluate the performance of the algorithm. The curve demonstrates that the proposed algorithm can achieve high detection rate with low false alarm rate preserved. The experimental results show that the proposed algorithm is simple, efficient and has high detection accuracy.
We give the equations of wave motion and evaluate the distribution of the polarization components of electric field. We also describe the calculation of the wave vector, and compared with the case of geometric approximation, we find the polarization state of light may not be maintained in transformation media.
This paper first introduces the basic principle of the four quadrant detector, and a set of laser positioning experiment system is built based on the four quadrant detector. Four quadrant laser positioning system in the actual application, not only exist interference of background light and detector dark current noise, and the influence of random noise, system stability, spot equivalent error can’t be ignored, so it is very important to system calibration and correction. This paper analyzes the various factors of system positioning error, and then propose an algorithm for correcting the system error, the results of simulation and experiment show that the modified algorithm can improve the effect of system error on positioning and improve the positioning accuracy.
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