Image registration is the process of geometric calibration of two or more images with overlapping areas of the same scene from different perspectives, different sensors or acquired at different times. This article focuses on the registration problem of sub-pixel displacement images in the process of super-resolution image reconstruction. Two sub-pixel image registration methods are introduced, including the spatial domain based feature matching SIFT registration method and the frequency domain based Vandewalle registration method. Four low resolution sequence images obtained through a micro scanning camera are used to simulate and analyze the registration accuracy of the two algorithms. The results show that both algorithms can achieve sub-pixel level registration of low resolution images.
Image registration is the process of geometric calibration of two or more images with overlapping areas of the same scene from different perspectives, different sensors or acquired at different times. This article focuses on the registration problem of sub-pixel displacement images in the process of super-resolution image reconstruction. Two sub-pixel image registration methods are introduced, including the spatial domain based feature matching SIFT registration method and the frequency domain based Vandewalle registration method. Four low resolution sequence images obtained through a micro scanning camera are used to simulate and analyze the registration accuracy of the two algorithms. The results show that both algorithms can achieve sub-pixel level registration of low resolution images.
This article provides theoretical derivation of the mathematical model of an infrared imaging system, and research shows that changing the sampling process of the detector can improve the MTF of the system. Theoretical simulation analysis showed that the use of micro scanning technology can improve the MTF of the system, and finally, the super-resolution ability of cc scanning technology was verified through experiments. The results indicate that the MTF of the system can be improved through micro scanning technology, and the main factors affecting the improvement of MTF include the pixel size of the detector, fill rate, micro scanning method and so on. When designing the system, different scanning methods can be set according to requirements to achieve super-resolution effects.
In infrared detection system, the range of field of view is a key index to judge the system. How to detect long distance targets with large field of view by technical means on the basis of existing devices has become an urgent problem to be solved. In this paper, the imaging principle of optical wedge scanning is firstly introduced, then infrared target is used to calibrate the infrared camera, and the distortion of the scanned image is corrected by using the calibration results. Finally, the optical wedge scanning can double the imaging field of view through the semi-physical simulation.
KEYWORDS: Signal to noise ratio, Signal detection, Ranging, Pulsed laser operation, Signal processing, Detection and tracking algorithms, Laser applications
Traditional laser ranging usually used threshold detection to obtain echo signal, so as to calculate the target distance. However, this method was not ideal for low SNR signal extraction. In order to solve the problem of laser ranging signal extraction under low SNR ratio. An algorithm based on multi-step continuous multiplication monopulse autocorrelation is presented. The peak-to-peak value is used to analyze the extraction effect of low SNR signal. The simulation results of the weak signal extraction algorithm are verified by experiments. The results show that the probability of successful extraction reaches 60%, when the SNR reaches 0.3, and the probability of successful extraction reaches 90%, when the SNR reaches 0.5.The validity of the algorithm is verified. The research provides a theoretical and experimental basis for the application of laser alarm signal detection in the future.
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