The simulated remote sensing image acquisition and restoration based on optical sparse aperture system

ZhenGuo Wang; YaXin Zhang; ZeXun Geng; XueLian Sui; Bing Li

doi:10.1117/12.807115

27 January 2009 The simulated remote sensing image acquisition and restoration based on optical sparse aperture system

ZhenGuo Wang, YaXin Zhang, ZeXun Geng, XueLian Sui, Bing Li

Proceedings Volume 7156, 2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments; 715616 (2009) https://doi.org/10.1117/12.807115
Event: International Conference of Optical Instrument and Technology, 2008, Beijing, China

Abstract

In spatial remote-sensing observation to the earth, the optical system aperture of satellite is becoming larger and larger. But, the larger aperture lead to the more limits constrained by manufacture costs and system loading. Optical sparse aperture imaging systems are composed of several smaller sub-apertures which are arrayed in some rules. But, because of the aperture of optical sparse aperture imaging system is just partial filling for the equivalent single large one, the system point spread function could be a certain spread and the response to middle-and-low spatial frequency is reduced. Consequently, the resolution of obtained images is blurred. So, the obtained images should be restored to improve image resolution. This paper takes advantage of an optical sparse aperture system established in the laboratory, imaging on an aviation remote-sensing negative, and then obtain the simulated optical sparse aperture remote-sensing images. Resolution of simulated sparse aperture remote-sensing images is greatly increased through the method presented by this paper, which incorporates the Laplacian factor in the increment Wiener filter. Through this image restoration process, the limitation of system itself is well compensated. Experiment results show that algorithm of this paper is proper to many kind of sparse system with different array structure and filling factor, the simulated remote-sensing images resolution and SNR (Signal and Noise Ratio) could be improved greatly.

Citation Download Citation

ZhenGuo Wang, YaXin Zhang, ZeXun Geng, XueLian Sui, and Bing Li "The simulated remote sensing image acquisition and restoration based on optical sparse aperture system", Proc. SPIE 7156, 2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments, 715616 (27 January 2009); https://doi.org/10.1117/12.807115

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KEYWORDS

Imaging systems

Remote sensing

Filtering (signal processing)

Image processing

Image resolution

Image restoration

Modulation transfer functions

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