@INPROCEEDINGS{13.whispers.constrained,
   author =  "Paul Honeine and Henri Lantéri",
   title =  "Constrained reflect-then-combine methods for unmixing hyperspectral data",
   booktitle =  "Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS)",
   address =  "Gainesville, Florida, USA",
   year  =  "2013",
   month =  "25 - 28~" # jun,
   acronym =  "WHISPERS",
   url_link= "https://ieeexplore.ieee.org/document/8080643",
   url_paper   =  "http://honeine.fr/paul/publi/13.whispers.cimmino.pdf",
   abstract={This paper deals with the linear unmixing problem in hyperspectral data processing, and in particular the estimation of the fractional abundances under sum-to-one and non-negativity constraints. For this purpose, we propose to adapt the reflect-then-combine iterative technique, initially derived by Cimmino. Several strategies are studied in order to handle the constraints, and experimental results are analyzed.}, 
   keywords={hyperspectral imaging, image processing, iterative methods, remote sensing, unmixing hyperspectral data, linear unmixing problem, hyperspectral data processing, reflect-then-combine iterative technique, Convergence, Optimization, Hyperspectral imaging, Mathematical model, Data processing, Estimation, Additives, Constrained optimization, hyperspectral data, unmixing problem, parallel projection, Cimmino's method}, 
   doi={10.1109/WHISPERS.2013.8080643}, 
   ISSN={2158-6276}, 
}

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