Six-parameter polarized BRDF Models were used to describe spectropolarimetric BRDF of cement board with experimental data. The nonlinear model parameters were obtained by genetic algorithm. The results show that the genetic algorithm has better performance and can get the nonlinear model parameters accurately. Through modeling analysis: cement board within visible spectrum shows the anisotropic characteristic, which is in consistency with the distribution regularity of polarized reflectance ratio factor of the target. In the region of the forward scattering, polarization are greatly influenced by observation geometry. Observing zenith Angle is smaller, the lower the degree of polarization, and with the increase of observing zenith Angle, polarization degree also increased gradually in the the principal plane. In back scattering range, there is also a local hot spot in the direction of the light source.
Firstly, the geometric model of linear sea surface is constructed based on linear wave theory and linear filtering method. At the same time, considering the nonlinear characteristics of sea waves, the modified model of nonlinear sea surface is introduced. By comparing the shape and statistical characteristics of nonlinear sea surface with linear sea surface, the Doppler echo spectrum of sea surface electromagnetic scattering is calculated, and the Doppler spectrum characteristics of dynamic sea surface scattering echo signals under different initial conditions are analyzed. Finally, the model simulation data are compared with the measured sea state data. The results show that the calculation results based on nonlinear sea surface are more consistent with the experimental data.
To solve the problem that infrared dim small targets are difficult to be detected and tracked under complex background,this paper proposes a method based on the fusion of Pipeline Filter and Kernelized Correlation Filter.First, preprocess the obtained image sequence to reduce the influence of complex background on target detection; then, detect dim small infrared moving targets based on Background Prediction and Pipeline Filter;Finally,track the targets by Kernelized Correlation Filter which is initialized by the obtained detection information.To deal with the interference caused by the lens moving, the target position is predicted in the process of targets tracking.The algorithm is verified by the constructed infrared dim target data set. The results show that the proposed algorithm has better robustness and realtime performance, and the tracking effect is obvious.
Aiming at the problem of the low contrast between target and background in the detected UAV target intensity images, a low-speed and small UAV targets detection and tracking method based on polarization imaging detection is proposed. Based on the analysis of the polarization imaging characteristics of low-speed and small UAV targets, through polarization image analysis, single-frame detection based on spatial filtering and adaptive threshold segmentation, continuous frame target trajectory association based on spatiotemporal information, and improved KCF algorithm Target tracking and other processing processes have realized the effective detection and tracking of low-speed and small UAV targets.
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