Martian aerosol abundance estimation based on unmixing of hyperspectral imagery

• Main Authors: Luo, Bin, Ceamanos, Xavier, Douté, Sylvain, Chanussot, Jocelyn
• Other Authors: GIPSA - Signal Images Physique (GIPSA-SIGMAPHY), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Laboratoire de Planétologie de Grenoble (LPG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2010
• Subjects: [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; Iceland
• Online Access: https://hal.science/hal-00578910; https://hal.science/hal-00578910/document; https://hal.science/hal-00578910/file/ieee_grss_10_Luo_Martian.pdf

International audience Classical linear unmixing approaches are not valid if the atmosphere and the aerosol are present in hyperspectral data, since the mixture model is no longer linear. In this paper, we present an iterative approach for estimating the abundance of aerosol based on unmixing of Martian hyperspectral data. On one hand, the results can provide the information on the aerosol of the Mars, which is very difficult to obtain. On the other hand, we can use the result to remove the effect of the aerosol on the original image and obtain more accurate linear unmixing results on the surface reflectance.