Multi video super-resolution algorithms reconstruct high spatio-temporal resolution video by exploiting complementary information in multiple low-resolution video sequences. Aiming at improving spatio-temporal resolution of video for real-world applications, an algorithm is proposed using Maximum Posterior Likelihood - Markov Random Field (MAP-MRF) and implemented on camera array. Compared with the current algorithms for super-resolution reconstruction, the suggested algorithm is advantageous in keeping the edge sharpness and detailed texture, and robust against the noises. The experimental result has confirmed the effectiveness of the proposed method under the practical conditions such as large displacement and motion aliasing.
Optical measuring angle data can be used in initial orbit determination. However, optical system has its magnitude limit, the initial orbits can not be determined when targets’ magnitudes are above the limited magnitude or the relative size of the target can not meet the resolution requirements. In order to expand the observable range of optical system and improve the accuracy of the orbit, it is necessary to improve the limited magnitude and the limited resolution of the system. This paper discusses the feasibility of initial orbit determination using camera array and provide the core processes of initial orbit determination using camera array. The experimental results show the effectiveness of the camera array to improve the system’s limited magnitude and the limited resolution.
Aiming to achieve the spatio-temporal alignment of multi sensor on the same platform for space target observation, a joint spatio-temporal alignment method is proposed. To calibrate the parameters and measure the attitude of cameras, an astronomical calibration method is proposed based on star chart simulation and collinear invariant features of quadrilateral diagonal between the observed star chart. In order to satisfy a temporal correspondence and spatial alignment similarity simultaneously, the method based on the astronomical calibration and attitude measurement in this paper formulates the video alignment to fold the spatial and temporal alignment into a joint alignment framework. The advantage of this method is reinforced by exploiting the similarities and prior knowledge of velocity vector field between adjacent frames, which is calculated by the SIFT Flow algorithm. The proposed method provides the highest spatio-temporal alignment accuracy compared to the state-of-the-art methods on sequences recorded from multi sensor at different times.
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