The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balan...The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.展开更多
To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded ...To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded as a nonlinear transformer realizing the mapping from the RGB color space to CIELAB color space. A variety of mapping accuracy were obtained with different network structures. BP neural networks can provide a satisfactory mapping accuracy in the field of color space transformation for video cameras.展开更多
The Extreme Ultraviolet Camera （EUVC） onboard the Chang＇e-3 （CE-3） lander is used to observe the structure and dynamics of Earth＇s plasmasphere from the Moon. By detecting the resonance line emission of helium i...The Extreme Ultraviolet Camera （EUVC） onboard the Chang＇e-3 （CE-3） lander is used to observe the structure and dynamics of Earth＇s plasmasphere from the Moon. By detecting the resonance line emission of helium ions （He＋） at 30.4 nm, the EUVC images the entire plasmasphere with a time resolution of 10 min and a spatial resolution of about 0.1 Earth radius （RE） in a single frame. We first present details about the data processing from EUVC and the data acquisition in the commissioning phase, and then report some initial results, which reflect the basic features of the plas- masphere well. The photon count and emission intensity of EUVC are consistent with previous observations and models, which indicate that the EUVC works normally and can provide high quality data for future studies.展开更多
基金Supported by National Natural Science Foundation of China（60873032, 61105095, 61203361） Doctoral Program Foundation of Ministry of Education of China （20100142110020）+3 种基金 the Specialized Research Fund for the Doctoral Program of Higher Education of China （20100073120020） Postdoctoral Science Foundation of China （2012M511095） Shanghai Municipal Natural Science Foundation （11ZR1418400） Shanghai Postdoctoral Science Foundation（12R21414200）
基金Project(J132012C001)supported by Technological Foundation of ChinaProject(2011YQ04013606)supported by National Major Scientific Instrument & Equipment Developing Projects,China
文摘The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.
文摘To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded as a nonlinear transformer realizing the mapping from the RGB color space to CIELAB color space. A variety of mapping accuracy were obtained with different network structures. BP neural networks can provide a satisfactory mapping accuracy in the field of color space transformation for video cameras.
文摘The Extreme Ultraviolet Camera （EUVC） onboard the Chang＇e-3 （CE-3） lander is used to observe the structure and dynamics of Earth＇s plasmasphere from the Moon. By detecting the resonance line emission of helium ions （He＋） at 30.4 nm, the EUVC images the entire plasmasphere with a time resolution of 10 min and a spatial resolution of about 0.1 Earth radius （RE） in a single frame. We first present details about the data processing from EUVC and the data acquisition in the commissioning phase, and then report some initial results, which reflect the basic features of the plas- masphere well. The photon count and emission intensity of EUVC are consistent with previous observations and models, which indicate that the EUVC works normally and can provide high quality data for future studies.
