The polarization phenomenon of the surface of an object and its changing in different spectra include its surface spatial geometric information and material information. Based on Kirchhoff law and Jones vector , the polarization model of the emission and reflection on the surface of the object is established, and the polarization phenomenon in infrared(IR) and visible light with different materials and incident angles are simulated. The IR and visible binocular polarization imaging system was constructed and the actual polarization data of small unmanned aerial vehicle(SUAV) and buildings were obtained. Two types of characteristic parameters, the degree of polarization and the angle of polarization, were extracted and analyzed, and the results proved that the SUAV and the background of the buildings had obvious differences in IR and visible. This research provides a basis for SUAV target detection and tracking using IR and visible polarization imaging in complex backgrounds.
This paper mainly studies the berthing ship target detection method of overhead-view image under the condition of a few training samples. Because of the limited training samples, we use the complete data set unrelated to the target detection task for pre-training to obtain a classification model, then expand the data according to a certain percentage and finally complete the training of the target detection model. This paper uses the idea of segmentation to solve the target detection problem. We adjusted the configuration of the region proposal network including the size of anchor frame and the threshold of non-maximum suppression according to the target morphology, so that the network generates a more accurate region of interest. Finally, the confidence levels, bounding-boxes and image masks of multi-objective generated concurrently. We performed experiments on self-made data sets which labeled from NWPU VHR-10 and produced good results, which proved the feasibility of this method in target detection of berthing ship target.
Infrared polarization results from infrared-emitted radiation and reflected radiation effects. Polarization generated by infrared reflection is perpendicularly polarized, whereas polarization generated by infrared emission is parallelly polarized. Using the polarization feature in different directions can enhance the detection and discrimination of the target. Based on the Stokes vector, the polarization degree and angle are obtained. Then, according to the analysis of the polarization states, an orthogonality difference method of extracting polarization features is proposed. An infrared intensity and polarization feature images are fused using an algorithm of nonsubsampled shearlets transformation. Image evaluation indices of the target contrast to background (C), average gradient (AG), and image entropy (E) are employed to evaluate the fused image and original intensity image. Results demonstrate that every index of the fused image with the polarization feature is significantly improved, thereby validating the effectiveness of the proposed target-enhancement approach using polarization features extracted by the orthogonal difference method.
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