High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.
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.
Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.
In order to resolve the difficult problem of detection and identification of optical targets in complex background or in long-distance transmission, this paper mainly study the range profiles of “cat-eye” targets using bi-spectrum. For the problems of laser echo signal attenuation serious and low Signal-Noise Ratio (SNR), the multi-pulse laser signal echo signal detection algorithm which is based on high-order cumulant, filter processing and the accumulation of multi-pulse is proposed. This could improve the detection range effectively. In order to extract the stable characteristics of the one-dimensional range profile coming from the cat-eye targets, a method is proposed which extracts the bi-spectrum feature, and uses the singular value decomposition to simplify the calculation. Then, by extracting data samples of different distance, type and incidence angle, verify the stability of the eigenvector and effectiveness extracted by bi-spectrum.
Space targets in astronomical images such as spacecraft and space debris are always in the low level of brightness and hold a small amount of pixels, which are difficult to distinguish from fixed stars. Because of the difficulties of space target information extraction, dynamic object monitoring plays an important role in the military, aerospace and other fields, track extraction of moving targets in short-exposure astronomical images holds great significance. Firstly, capture the interesting stars by region growing method in the sequence of short-exposure images and extract the barycenter of interesting star by gray weighted method. Secondly, use adaptive threshold method to remove the error matching points and register the sequence of astronomical images. Thirdly, fuse the registered images by NCST-PCNN image fusion algorithm to hold the energy of stars in the images. Fourthly, get the difference of fused star image and final star image by subtraction of brightness value in the two images, the interesting possible moving targets will be captured by energy accumulation method. Finally, the track of moving target in astronomical images will be extracted by judging the accuracy of moving targets by track association and excluding the false moving targets. The algorithm proposed in the paper can effectively extract the moving target which is added artificially from three images or four images respectively, which verifies the effectiveness of the algorithm.
As the commercial performance of camera sensor and the imaging quality of lens improving, it has the possibility to applicate in the space target observation. Multiple cameras can further improve the detection ability of the camera with image fusion. This paper mainly studies the multiple camera image fusion problem of registration with the imaging characteristics of a commercial camera, and then put forward an applicable method of star image registration. It proved that the accuracy of registration could reach the subpixel level with experiments.
Proc. SPIE. 9297, International Symposium on Optoelectronic Technology and Application 2014: Laser and Optical Measurement Technology; and Fiber Optic Sensors
KEYWORDS: Signal to noise ratio, Optical filters, Laser range finders, Laser processing, Laser applications, Interference (communication), Signal processing, Electronic filtering, Signal detection, Filtering (signal processing)
The multi-pulsed laser ranging technology is prominent on improving the maximum measuring range of laser active detection，laser range finder and other long-distance measurement. For all laser echo detection techniques, the weak signal detection is an important step, which aims to increase the detection range. Most algorithms are based on the priori knowledge of laser echo or the improvement of laser power. However, we cannot know or estimate the waveform accurately in many applications. Moreover, these means are difficult to satisfy the real-time needs. The present paper proposes an improved algorithm which extended the signal accumulation algorithm for the high power burst laser. This method is mainly based on signal accumulation and tri-cumulant algorithm which can improve the signal to noise SNR of the weak laser echo; moreover it does not need more prior knowledge of echo. In order to reduce the detection time, the algorithm is realized based on FPGA using signal retiming and parallel pipeline structure. The simulations and experiments results demonstrate that the minimum detecting SNR is -5dB and the maximum detecting time is only less than 1us.
The laser stealth of space target is useful, important and urgent in practice. This paper introduces the definition expression of laser radar cross section (LRCS) and the general laws of the influencing factors of space target’s LRCS, including surface materials types, target’s shape and size. Then this paper discusses the possible laser stealth methods of space target in practical applications from the two view points of material stealth methods and shape stealth methods. These conclusions and suggestions can provide references for the next research thinking and methods of the target’s laser stealth.