Aiming at the problem that the background noise mixed in the target echo will affect the calculation of the target polarization degree when the traditional polarization detection system obtains the target polarization degree, based on the polarization Gm-APD detection model, a set of target echo polarization correction method is proposed. The target is imaged in a xenon lamp environment, the influence of target attitude and polarization angle on detection is explored, and the polarization imaging results are analyzed. The results show that the polarization system has a significant effect on metal materials with low surface roughness. When circularly polarized light is incident, the echo trigger probability of the metal material reaches a peak at the polarization angle of 135°. The greater the incident angle, the greater the echo depolarization and the lower the trigger probability. By inverting the distribution of echo photons, the number of background noise photons in the echo and the number of target echo photons can be obtained respectively, and a more accurate correction of the polarization degree of the target echo can be obtained. For metal materials, when the target attitude angle is 30°, the target polarization before and after correction are 0.47 and 0.57 respectively, and the target echo polarization after correction is 7% higher than that without correction. This research work provides experimental support for the effective detection and target detection of GM-APD lidar in the daytime.
Edges are critical important for the visual appearance of images. The traditional denoising algorithms are difficult to preserve the edges of the image while removing the noise of ICCD sensing image. At the same time, it is difficult to eliminate the problems of image darkness and low resolution caused by uneven illumination. This paper proposes a multilevel filtering image denoising algorithm based on edge information fusion. The target edges detection of the image after non-local means (NL-means) filtering is carried out based on the eight-direction Sobel operator. In order to filter the false edge points and residual noise, an adaptive threshold is determined according to the mean and variance of the eight neighborhood pixels of the detected pixel. Meanwhile, homomorphic filtering is used to enhance the image contrast and uniformity. By comparing the pixel values of the edge image and the homomorphic filtered image, the final denoised image is obtained by fusing the two images. The results indicate that, compared with the traditional algorithms, the edge preserving ability of the proposed algorithm is improved by more than 20%, and the denoising ability is improved by 63.5% for building target. For specific targets (vehicle), the results demonstrate that the proposed algorithm have the maximum edge preserving index and contrast, and the minimum non-uniformity. This algorithm lays a foundation for target segmentation and recognition.
Aiming at the problem that the Geiger-mode Avalanche Photodiode (GM-APD) is susceptible to background noise and the detection effect decreases during the day, based on the polarization GM-APD detection model, a set of GM-APDbased polarized lidar imaging experimental equipment is proposed. Using this equipment to image the target in the simulated sunlight environment, the effect of polarization detection on the echo triggering performance was studied. The results show that, compared with the non-polarized system, the polarized system reduces the impact of noise on target detection, improves the image quality, and reduces the false alarm probability of the image. When the laser single pulse energy is 400nJ, and the polarization angle is 135° , the trigger probability of the metal plate is increased by 10.5%, and its false alarm probability is reduced by 4.6%; the trigger probability of the rough wood board is reduced by 15.2%, and its false alarm probability is reduced 8.9%.Due to the deterioration of imaging results caused by background noise, it is proposed to use polarization degree images for further background filtering to extract a more complete target contour. This research work provides experimental support for the effective detection of GM-APD lidar during the day.
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