A Survey of Spectral Unmixing Algorithms

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Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained Nonnegative Matrix Factorization (2011, methodology): “ing fractional abundances, is often employed to preprocess hyperspectral data [1].”
Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion (2012, background): “In recent decades, many hyperspectral unmixing techniques based on a linear spectral mixture model have been developed [20]–[30].”
Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization (2007, background): “During the past few decades, a great deal of endmember extraction algorithms has been proposed [2].”
Digital imaging in pathology: whole-slide imaging and beyond. (2013, background): “, when stains do not obey Beer’s law (82)].”
Hyperspectral Subspace Identification (2008, background): “The dimension reduction flowchart of ORASIS can be found in [39].”