Paper
24 September 2012 The optical synthetic aperture image restoration based on the improved maximum-likelihood algorithm
Zexun Geng, Qing Xu, Baoming Zhang, Zhihui Gong
Author Affiliations +
Abstract
Optical synthetic aperture imaging (OSAI) can be envisaged in the future for improving the image resolution from high altitude orbits. Several future projects are based on optical synthetic aperture for science or earth observation. Comparing with equivalent monolithic telescopes, however, the partly filled aperture of OSAI induces the attenuation of the modulation transfer function of the system. Consequently, images acquired by OSAI instrument have to be post-processed to restore ones equivalent in resolution to that of a single filled aperture. The maximum-likelihood (ML) algorithm proposed by Benvenuto performed better than traditional Wiener filter did, but it didn't work stably and the point spread function (PSF), was assumed to be known and unchanged in iterative restoration. In fact, the PSF is unknown in most cases, and its estimation was expected to be updated alternatively in optimization. Facing these limitations of this method, an improved ML (IML) reconstruction algorithm was proposed in this paper, which incorporated PSF estimation by means of parameter identification into ML, and updated the PSF successively during iteration. Accordingly, the IML algorithm converged stably and reached better results. Experiment results showed that the proposed algorithm performed much better than ML did in peak signal to noise ratio, mean square error and the average contrast evaluation indexes.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zexun Geng, Qing Xu, Baoming Zhang, and Zhihui Gong "The optical synthetic aperture image restoration based on the improved maximum-likelihood algorithm", Proc. SPIE 8451, Software and Cyberinfrastructure for Astronomy II, 845139 (24 September 2012); https://doi.org/10.1117/12.925301
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KEYWORDS
Point spread functions

Image restoration

Imaging systems

Reconstruction algorithms

Modulation transfer functions

Filtering (signal processing)

Inverse optics

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