pyramid algorithm and grid algorithm are typical algorithms for all-sky autonomous star identification, and it has advantages of high recognition rate, and fast in running. However their recognition rate decreases rap...
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ISBN:
(数字)9781510614062
ISBN:
(纸本)9781510614062;9781510614055
pyramid algorithm and grid algorithm are typical algorithms for all-sky autonomous star identification, and it has advantages of high recognition rate, and fast in running. However their recognition rate decreases rapidly when the position noise, lost stars or fake stars exist in the star image. In order to improve the performance of star sensor, a new star identification algorithm based on star pattern of wheel code is proposed. The algorithm combines the main star and its surrounding neighbor stars to form the characteristic unit, and then constructs the corresponding code feature and the wheel feature respectively. In the process of star matching, the algorithm uses the code feature of the observation star as an index to Inquire storage address of the candidate navigation star, and then calculates the similarity of wheel feature between the candidate navigation star and the observation. Simulation shows that: compared to the grid algorithm, this algorithm has higher rate of correct star recognition and better robustness. When the position error is 1 pixel and 2 lost stars exist in star image, this algorithm can reach 98.4% on identification rate, while the grid algorithm is 94.6%, and the pyramid algorithm is 83.5%;when the position error is 1 pixel and 2 fake stars exist in star image, this algorithm can reach 98.6% on identification rate, while the grid algorithm is 92.3%, and the pyramid algorithm is 87.2%.
To get high precision attitude for space telescope, a double marginal FOV (field of view) FGS (Fine Guide Sensor) is proposed. It is composed of two large area APS CMOS sensors and both share the same lens in main lig...
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ISBN:
(数字)9781510619487
ISBN:
(纸本)9781510619487
To get high precision attitude for space telescope, a double marginal FOV (field of view) FGS (Fine Guide Sensor) is proposed. It is composed of two large area APS CMOS sensors and both share the same lens in main light of sight. More star vectors can be get by two FGS and be used for high precision attitude determination. To improve star identification speed, the vector cross product in inter-star angles for small marginal FOV different from traditional way is elaborated and parallel processing method is applied to pyramid algorithm. The star vectors from two sensors are then used to attitude fusion with traditional QUEST algorithm. The simulation results show that the system can get high accuracy three axis attitudes and the scheme is feasibility.
Image mosaicing has been used in various arenas of image engineering. The main purpose of this research work is to develop a novel blending algorithm for mosaicing of two non-overlapping images with minimum distortion...
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ISBN:
(纸本)9781479922765
Image mosaicing has been used in various arenas of image engineering. The main purpose of this research work is to develop a novel blending algorithm for mosaicing of two non-overlapping images with minimum distortion and no visible seam. In the proposed method, images are mosaiced using the pyramid technique and Savitzky-Golay filter is used for smoothing the seam between the images in the generated mosaic. Savitzky-Golay filter, is based on the least square fitting of polynomial functions of image intensities. It effectively reduces the noise and preserves the image information content resulting in a visually pleasing mosaiced image. The results and comparative analysis show the effectiveness of the proposed method.
Due to a limited dynamic range of widely used image recorders, it is difficult to record complete information on real scenes using a single image, and a restricted range of contrast, brightness and chromaticity can on...
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Due to a limited dynamic range of widely used image recorders, it is difficult to record complete information on real scenes using a single image, and a restricted range of contrast, brightness and chromaticity can only be recorded. To mitigate this matter, a set of images of the identical scenery could be firstly captured at different exposure situations, and next be merged into an informative image via image fusion. In the paper, we present a well details-preserving image fusion technique via improved exposure evaluation and dual-pyramid model. The proposed method owning to its advantages of cost-effective, computation-stable and adaptive image processing can achieve a high dynamic range image from a set of multiple exposure sequences even for extremely complicated scenes. Experimental results demonstrated that the proposed method has richer details and better visual effects compared with the other commonly used techniques in most cases. Therefore, it could provide useful help and inspiration for image processing and enhancement field such as digital photography, remote sensing and medical imaging.
Wavelets, which are used to separate data into different components, have many applications. Steganography, one such application, is a form of secret communication where the existence of a message is concealed. Method...
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A simple method which for generalizing the classical orthonormal wavelets is presented using investigation of the simplest Haar scaling function. A new kind of orthonormal wavelets is constructed from a classical orth...
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A simple method which for generalizing the classical orthonormal wavelets is presented using investigation of the simplest Haar scaling function. A new kind of orthonormal wavelets is constructed from a classical orthonormal wavelets using the method proposed in this paper. These new wavelets inherit some basic properties of the corresponding classical wavelets, such as the orthonormality, the order of regularity, the time-frequency localization characteristics, and so on. meanwhile some performances of the new wavelets are improved. The generalized Haar wavelet, the generalized Shannon wavelet and the generalized Meyer wavelet, the generalized Daubechies wavelets are discussed emphatically. Finally, based on the new wavelet system, some fast algorithms for analytic wavelet transform analysis of real signals are studied.
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