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Remote Sens. 2015, 7(10), 13190-13207; doi:10.3390/rs71013190

Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing

German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), 82234 Wessling, Germany
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Academic Editors: Saskia Foerster, Véronique Carrere, Michael Rast, Karl Staenz and Prasad S. Thenkabail
Received: 23 June 2015 / Revised: 9 September 2015 / Accepted: 28 September 2015 / Published: 5 October 2015
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Abstract

This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described method independently decomposes each image element into a set of representative spectra, which come directly from the image and have previously undergone a low-pass filtering in noisy bands. The residual vector from the unmixing process is considered as mostly composed of noise and ignored in the reconstruction process. The first assessment of the results is encouraging, as the original bands taken into account are reconstructed with a high signal-to-noise ratio and low overall distortions. Furthermore, the same method could be applied for the inpainting of dead pixels, which could affect EnMAP data, especially at the end of the satellite’s life cycle. View Full-Text
Keywords: EnMAP; denoising; spectral unmixing; sparse reconstruction; inpainting; dead pixels EnMAP; denoising; spectral unmixing; sparse reconstruction; inpainting; dead pixels
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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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MDPI and ACS Style

Cerra, D.; Bieniarz, J.; Müller, R.; Storch, T.; Reinartz, P. Restoration of Simulated EnMAP Data through Sparse Spectral Unmixing. Remote Sens. 2015, 7, 13190-13207.

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