ing at the problems of low precision and slow speed of the traditional reconstruction algorithms, we propose a regularization priori based fast all variation algebraic iteration (ARTTV) algorithm to improve the reconstruction precision of the symmetric and asymmetric flames. Further, to improve the reconstruction speed, we establish an extreme learning machine neural network based on the “ARTTV-particle swarm algorithm kernel”, which exhibits approximately the same reconstruction ability as that of the iterative algorithm. The construction speed of the proposed algorithm is approximately 300 times that of the iterative algorithm.
.ing at the problem of the complexity of the existing global calibration method for multi-camera system with non-overlapping fields, an accurate calibration method with non-overlapping fields of view (FOV) cameras based on spatial constraints is proposed. Firstly, spliced small targets distributed in the field of respective camera are fixed together to make up a large calibration planar. A large-field camera is used to measure the spliced small targets, and the obtained relationship between the calibration plates is used as the correlated parameter between cameras. Then, small targets in the fields of view are obtained by non-overlapping FOV cameras, the reprojection error functions of cameras can be obtained based on spatial constraints, and the transformation matrix between non-overlapping FOV cameras is nonlinearly optimized by the Levenberg-Marquardt algorithm. The experimental results show that the reprojection errors of the global calibration method are 0.33 mm and 0.57 mm for the X-axes and Y-axes, respectively. It achieves global calibration of non-overlapping FOV cameras with high precision and stability.
.show that the uncertainty of the calibration approach is less than 3.6%. The difference in calibration coefficient between the WDTMLR method and the reflectance-based method is less than 5.5%. Moreover, the difference between the reflectivity and radiance of ground object obtained by the satellite sensor and that of field measured value is less than 6%, which demonstrate the effectiveness of on-orbit radiometric calibration. The WDTMLR method can satisfy with the application requirements for high-precision on-orbit calibration in complex environmental conditions.
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