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Proceedings Paper

Detection algorithm for space dim moving object
Author(s): Hai-Bin Pan; Wei Zhang; Ming-Yu Cong
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Paper Abstract

Dim object detection is the key technology to space objects surveillance. The space detection data model (SDDM) and space dim moving object detection algorithm (SDMODA) are investigated systematically in this paper. SDDM is set up, which consists of the circuit Gaussian noise, dark current Poisson noise, background light Poisson noise, non-moving objects noise and moving object signal sub-model. By digital simulation, time sequence image data of each CCD pixel is built to input SDMODA as raw data. SDMODA computes maximum value projection, pixel average and pixel standard deviation in each CCD pixel of every time sequence data. By subtracting pixel average from maximum value projection and then divided by pixel standard deviation in each pixel, SDMODA produces a new standard frame. The standard frame is processed to find candidate object streaks by threshold filter, which can eliminate non-moving objects and suppress the circuit Gaussian noise, dark current Poisson noise and background light Poisson noise. Since the invariability of object streak in streak angle and streak length, SDMODA can eliminate false streaks and find true object streak. By simulation experiment, SDDM can produce time sequence data with different signal-to-noise ratio and SDMODA can detect object streak with signal-to-noise ratio of 3.5dB.

Paper Details

Date Published: 5 March 2007
PDF: 8 pages
Proc. SPIE 6595, Fundamental Problems of Optoelectronics and Microelectronics III, 65951H (5 March 2007); doi: 10.1117/12.725734
Show Author Affiliations
Hai-Bin Pan, Harbin Institute of Technology (China)
Wei Zhang, Harbin Institute of Technology (China)
Ming-Yu Cong, Harbin Institute of Technology (China)


Published in SPIE Proceedings Vol. 6595:
Fundamental Problems of Optoelectronics and Microelectronics III

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