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Article

Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization

Department of Civil Engineering, University of Seoul, Seoul 02504, Korea
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Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(20), 4444; https://doi.org/10.3390/app9204444
Received: 24 September 2019 / Revised: 15 October 2019 / Accepted: 17 October 2019 / Published: 19 October 2019
In most hyperspectral super-resolution (HSR) methods, which are techniques used to improve the resolution of hyperspectral images (HSIs), the HSI and the target RGB image are assumed to have identical fields of view. However, because implementing these identical fields of view is difficult in practical applications, in this paper, we propose a HSR method that is applicable when an HSI and a target RGB image have different spatial information. The proposed HSR method first creates a low-resolution RGB image from a given HSI. Next, a histogram matching is performed on a high-resolution RGB image and a low-resolution RGB image obtained from an HSI. Finally, the proposed method optimizes endmember abundance of the high-resolution HSI towards the histogram-matched high-resolution RGB image. The entire procedure is evaluated using an open HSI dataset, the Harvard dataset, by adding spatial mismatch to the dataset. The spatial mismatch is implemented by shear transformation and cutting off the upper and left sides of the target RGB image. The proposed method achieved a lower error rate across the entire dataset, confirming its capability for super-resolution using images that have different fields of view. View Full-Text
Keywords: hyperspectral image; super-resolution; histogram equalization hyperspectral image; super-resolution; histogram equalization
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MDPI and ACS Style

Kim, B.; Cho, S. Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization. Appl. Sci. 2019, 9, 4444. https://doi.org/10.3390/app9204444

AMA Style

Kim B, Cho S. Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization. Applied Sciences. 2019; 9(20):4444. https://doi.org/10.3390/app9204444

Chicago/Turabian Style

Kim, Byunghyun, and Soojin Cho. 2019. "Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization" Applied Sciences 9, no. 20: 4444. https://doi.org/10.3390/app9204444

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