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Sensors 2017, 17(1), 82; doi:10.3390/s17010082

Hyperspectral Imagery Super-Resolution by Adaptive POCS and Blur Metric

1
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
2
Ministry of Education Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China
3
Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai 810016, China
*
Author to whom correspondence should be addressed.
Academic Editors: Cheng Wang, Julian Smit, Ayman F. Habib and Michael Ying Yang
Received: 15 October 2016 / Revised: 26 November 2016 / Accepted: 23 December 2016 / Published: 3 January 2017
(This article belongs to the Special Issue Multi-Sensor Integration and Fusion)
View Full-Text   |   Download PDF [4668 KB, uploaded 3 January 2017]   |  

Abstract

The spatial resolution of a hyperspectral image is often coarse as the limitations on the imaging hardware. A novel super-resolution reconstruction algorithm for hyperspectral imagery (HSI) via adaptive projection onto convex sets and image blur metric (APOCS-BM) is proposed in this paper to solve these problems. Firstly, a no-reference image blur metric assessment method based on Gabor wavelet transform is utilized to obtain the blur metric of the low-resolution (LR) image. Then, the bound used in the APOCS is automatically calculated via LR image blur metric. Finally, the high-resolution (HR) image is reconstructed by the APOCS method. With the contribution of APOCS and image blur metric, the fixed bound problem in POCS is solved, and the image blur information is utilized during the reconstruction of HR image, which effectively enhances the spatial-spectral information and improves the reconstruction accuracy. The experimental results for the PaviaU, PaviaC and Jinyin Tan datasets indicate that the proposed method not only enhances the spatial resolution, but also preserves HSI spectral information well. View Full-Text
Keywords: image blur metric; Gabor wavelet transform; weighted POCS; hyperspectral imagery; super-resolution image blur metric; Gabor wavelet transform; weighted POCS; hyperspectral imagery; super-resolution
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Hu, S.; Zhang, S.; Zhang, A.; Chai, S. Hyperspectral Imagery Super-Resolution by Adaptive POCS and Blur Metric. Sensors 2017, 17, 82.

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