Ensemble des solutions parcimonieuses exactes en démélange spectral : algorithme garanti et analyse des solutions
Abstract
We focus on the exact resolution of sparse spectral unmixing problems, that is, the search for cardinality-limited linear least squares solutions under non-negativity and sum-to-one constraints. The originality of the proposed method - for which the Python code is provided - lies in its multisolution nature; we return the set of supports that yield the best solutions. The method is tested on synthetic data, with promising results.
Type
Publication
In GRETSI 2025.
