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Sensors 2017, 17(9), 2142; https://doi.org/10.3390/s17092142

Multi-Frame Super-Resolution of Gaofen-4 Remote Sensing Images

National University of Defense Technology, College of Opto-Electronic Science and Engineering, Deya Road 109, Changsha 410073, China
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Received: 26 July 2017 / Revised: 4 September 2017 / Accepted: 14 September 2017 / Published: 18 September 2017
(This article belongs to the Section Remote Sensors)
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Abstract

Gaofen-4 is China’s first geosynchronous orbit high-definition optical imaging satellite with extremely high temporal resolution. The features of staring imaging and high temporal resolution enable the super-resolution of multiple images of the same scene. In this paper, we propose a super-resolution (SR) technique to reconstruct a higher-resolution image from multiple low-resolution (LR) satellite images. The method first performs image registration in both the spatial and range domains. Then the point spread function (PSF) of LR images is parameterized by a Gaussian function and estimated by a blind deconvolution algorithm based on the maximum a posteriori (MAP). Finally, the high-resolution (HR) image is reconstructed by a MAP-based SR algorithm. The MAP cost function includes a data fidelity term and a regularized term. The data fidelity term is in the L2 norm, and the regularized term employs the Huber-Markov prior which can reduce the noise and artifacts while preserving the image edges. Experiments with real Gaofen-4 images show that the reconstructed images are sharper and contain more details than Google Earth ones. View Full-Text
Keywords: super-resolution; blind deconvolution; remote sensing; staring imaging; MAP super-resolution; blind deconvolution; remote sensing; staring imaging; MAP
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Xu, J.; Liang, Y.; Liu, J.; Huang, Z. Multi-Frame Super-Resolution of Gaofen-4 Remote Sensing Images. Sensors 2017, 17, 2142.

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