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Parallel implementation of unmixing algorithm for variable-endmember linear mixture model

2010 IEEE International Geoscience and Remote Sensing Symposium, 2010
This study introduces a parallel implementation of unmixing algorithm for a variable-endmember linear mixture model (VELMM). The model had been developed to retrieve leaf area index (LAI) and fraction of vegetation cover (FVC) from remotely sensed surface reflectance.
Naoki Takahashi +3 more
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Unmixing based Change Detection for Hyperspectral Images with Endmember Variability

2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2018
Unmixing based change detection (UBCD) provides subpixel level information on the nature of the changes that occur in a temporal image series, in addition to providing a multi-output change detection map. These advantages have recently carried UBCD to prominence among change detection approaches for hyperspectral images.
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Endmember variability resolved by pixel purity index in hyperspectral imagery

SPIE Proceedings, 2014
Endmember variability presents a great challenge in endmember finding since a true endmember may be contaminated by many unknown factors. This paper develops a pixel purity index (PPI) based approach to resolving this issue. It is known that endmember candidates must have their PPI counts greater than 0.
Yao Li +3 more
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Manifold Regularized Sparse Archetype Analysis Considering Endmember Variability