Hadamard coding spectral imaging technology is a computational spectral imaging technology, which modulates the target’s spectral information and recovers the original spectrum by inverse transformation. Because it has the advantage of multichannel detection, it is being studied by more researchers. For the engineering realization of push-broom coding spectral imaging instrument, it will inevitably be subjected to push-broom error, template error and detection noise, the redundant sampling problem caused by detector. Therefore, three restoration methods are presented in this paper: firstly, the one is the least squares solution, the two is the zero-filling inverse solution by extending the coding matrix in the redundant coding state to a complete higher order Hadamard matrix, the three is sparse method. Secondly, the numerical and principle analysis shows that the inverse solution of zero-compensation has better robustness and is more suitable for engineering application; its conditional number, error expectation and covariance are better and more stable because it directly uses Hadamard matrix, which has good generalized orthogonality. Then, a real-time spectral reconstruction method is presented, which is based on inverse solution of zero-compensation. Finally, simulation analysis shows that spectral data could be destructed relative accuracy in the error condition; however, the effect of template noise and push error on reconstruction is much greater than that of detection error. Therefore, in addition to reducing the detection noise as much as possible, lower template noise and more accurate push controlling should be guaranteed specifically in engineering realization.

.Measuring the pose of non-cooperative targets in space is a critical supporting technology for cleaning up space debris and recovering items. However, most existing methods are simulation experiments conducted in good lighting environments and tend to show poor performance in dark lighting environments. A target pose measurement method based on binocular vision is proposed, which is suitable for dark lighting environments. First, the traditional features from accelerated segment test algorithm are improved to reduce the influence of illumination on the performance of feature point extraction under various postures. The point feature and line feature are combined to extract image features more easily in a dark lighting environment while retaining the high accuracy of the pose measurement algorithm based on point features. Second, the normalized cross-correlation coefficient matching method is combined with the epipolar constraint to narrow the search range of the matching points from the two-dimensional plane to the epipolar line, which substantially improves the matching efficiency and accuracy of the matching algorithm. Finally, post-processing through feature matching is performed to reduce the probability of mismatches. Simulation and physical experiment results show that our method can stably extract features and obtain high-precision target pose information in well-illuminated as well as dark lighting environments, making it suitable for high-precision target pose measurement under insufficient illumination.

Infrared imaging technology is widely used in national defense, industry, medical and other fields. High performance infrared imaging technology is highly valued by all countries in the world. However, the inhomogeneity, the inherent characteristic of infrared image, will seriously affect the real information of the image and seriously restrict the performance of infrared imaging system. In this paper, we proposed a shutter-less non-uniformity correction (SLNUC) algorithm based on ambient temperature. The SLNUC is based on the non-uniformity correction of the collected image of HgCdTE mid-wave infrared detector. The experimental results show that the SLNUC correction algorithm can adapt to the working requirements of a wide temperature range, without affecting the output of video stream, and the non-uniformity reaches 0.17% after correction, which lays a foundation for the development of new equipment.

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