Hyperspectral Imagery Superresolution

Date

2016-05-19

Author

Irmak, Hasan
Akar, Gözde
Yuksel, Seniha Esen

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Despite their high spectral resolution, hyperspectral images have low spatial resolution which adversely affects the applications that use hyperspectral images. In this study, instead of the traditional way of using spectral images, abundances of the endmembers are used in resolution enhancement. In the proposed method, first, endmembers are extracted with the SISAL algorithm. Then, the abundance maps are estimated using FCLS. From the low resolution abundance maps, high resolution abundance maps are obtained with a total variation based minimization. Finally, high resolution hyperspectral images are constructed from high resolution abundance maps. The proposed method is tested on real hyperspectral images. The experimental results and comparative analysis show the effectiveness of the proposed method.

Subject Keywords

Hyperspectral, Total variation minimization, Endmember, Abundance maps

URI

https://hdl.handle.net/11511/54710

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

H. Irmak, G. Akar, and S. E. Yuksel, “Hyperspectral Imagery Superresolution,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54710.