Image enhancement for space object based on information between adjacent spatial-temporal frames

Zhang Zhi; Sun Quansen; Lin Xuling; Han Mingliang

doi:10.3788/IRLA201948.S128004

Usually the ability of the space optical camera is degraded by many factors during operation on orbit for the space object observation. The result is induced by variation of some prior parameters such as platform motion, attitude variation, jitter and drift angle during operation on orbit. So it is not satisfying to improve the image quality, only by using the parameters measured on the ground test such as the point response function of the infrared CCD camera. The simulation for the space object observation of the on-board imaging system and the enhancement is proposed here, combining with the information between adjacent spatial and temporal frames. The dynamic model is formulated, representing the characteristic of point response function during multiple exposure times. Furthermore, the enhancement algorithm is proposed based on the correlated information between two adjacent spatial and temporal frames. The norm optimization method is used in the frequency domain. The dynamic point response function of the space object observation system is simulated in the experiment. And the detecting spectrum range is mid-Infrared. The processed result is clear and sharp by the proposed method. The experimental result shows that the proposed method is better than the conventional methods.

Image enhancement for space object based on information between adjacent spatial-temporal frames

1. School of Computer Science and Engineering,Nanjing University of Science & Technology,Nanjing 210094,China;

2. Beijing Institute of Space Mechanic & Electricity,Beijing 100094,China;

3. Beijing Key Laboratory of Advanced Optical Remote Sensing Technology,Beijing 100094,China;

4. Anhui Province Natural Gas Development Co.,ltd.,Hefei 230011,China

Received Date: 2018-11-07

Rev Recd Date: 2018-12-12

Publish Date: 2019-04-25

Key words:

Abstract: Usually the ability of the space optical camera is degraded by many factors during operation on orbit for the space object observation. The result is induced by variation of some prior parameters such as platform motion, attitude variation, jitter and drift angle during operation on orbit. So it is not satisfying to improve the image quality, only by using the parameters measured on the ground test such as the point response function of the infrared CCD camera. The simulation for the space object observation of the on-board imaging system and the enhancement is proposed here, combining with the information between adjacent spatial and temporal frames. The dynamic model is formulated, representing the characteristic of point response function during multiple exposure times. Furthermore, the enhancement algorithm is proposed based on the correlated information between two adjacent spatial and temporal frames. The norm optimization method is used in the frequency domain. The dynamic point response function of the space object observation system is simulated in the experiment. And the detecting spectrum range is mid-Infrared. The processed result is clear and sharp by the proposed method. The experimental result shows that the proposed method is better than the conventional methods.

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Reference (15)

[1]	Eekeren A W M V, Schutte K, Vliet L J V. Multi-frame super-resolution reconstruction of small moving objects[J]. IEEE Trans on Image Process, 2010, 19(11):2901-2912.
[2]	Zhou S, Yuan Y, Su L, et al. Multiframe super resolution reconstruction method based on light field angular images[J]. Opt Commun, 2017, 404(1):189-195.
[3]	Tarde R W, Donley E, Carr J L. Modeling and optimal design of optical remote sensing payloads[C]//Earth Observing Systems XⅡ, Proc of SPIE, 2007, 6677:1G1-1G12.
[4]	Iwasaki A. Detection and estimation of satellite attitude jitter using remote sensing imagery[C]//Advances in Spacecraft Technologies in Tech, 2010:257-272.
[5]	Zhi Z, Jun L Z. A geometry model based on space motion imaging[C]//The 4th International Symposium on Photoelectronic Detection and Imaging:Advances in Imaging Detectors and Applications, Proc of SPIE, 2011, 8194:81941J.
[6]	Zhang L, Sun Z Y, Jin G. Design of physical simulation system for TDICCD dynamic imaging[J]. Optics and Precision Engineering, 2011, 19(3):641-650.
[7]	Burrows C J. Hubble space telescope optics status[J]. Applications of Digital Image Processing XIV, 1991, 1567:284-293.
[8]	Succary R, Cohena A, Yaractzr P, et al. A dynamic programming algorithm for point target detection:practical parameters for DPA[J]. Signal and Data Processing of Small Targets, 2001, 4473:96-100.
[9]	Kee E, Paris S, Chen S, et al. Modeling and removing spatially-varying optical blur[C]//IEEE ICCP, 2011:1-8.
[10]	Schuler C J, Hirsch M, Harmeling S, et al. Non-stationary correction of optical aberrations[C]//Computer Vision (ICCV), IEEE International Conference, 2011:659-666.
[11]	Levin A, Weiss Y, Durand F, et al. Understanding and evaluating blind deconvolution algorithms[C]//Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, 2009:1964-1971.
[12]	Tang S, Gong W G, Li W H, et al. Non-blind image deblurring method by local and nonlocal total variation models[J]. Signal Processing, 2014, 94:339-349.
[13]	Javaran T A, Hassanpour H, Abolghasemi V. Non-blind image deconvolution using a regularization based on re-blurring process[J]. Computer Vision and Image Understanding, 2017, 154:16-34.
[14]	Zhang Z, Lin X L, Zhang J B, et al. Improvement method for terahertz imaging quality[J]. Infrared and Laser Engineering, 2017, 46(11):1126002.
[15]	Zhao Y H, Wang Y Y, Luo H B, et al. New technique for dynamic-range compression and contrast enhancement in infrared imaging systems[J]. Infrared and Laser Engineering, 2018, 47(S1):S126001.

Image enhancement for space object based on information between adjacent spatial-temporal frames

doi: 10.3788/IRLA201948.S128004

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