@incollection{fdi:010070173,
  title = {{S}pectral-spatial unmixing approaches in hyperspectral {VNIR}/{SWIR} imaging},
  author = {{G}orretta, {N}. and {G}omez, {C}{\'e}cile},
  editor = {},
  language = {{ENG}},
  abstract = {{S}pectral unmixing refers to the process by which the spectrum measured over a mixed target is decomposed into a collection of pure component spectra called endmembers and their fractional abundances. {M}ixed targets are frequently encountered in remote sensing and spectral unmixing techniques have been mostly developed for visible and near-infrared (400–1000 nm) and short-wave infrared (1000–2500 nm) remote sensing. {T}he first unmixing studies were based on the implicit assumption that the spatial distribution of endmembers is random, and therefore, each mixed pixel is spatially independent. {H}ence, only the spectral dimension was taken into account in the unmixing process. {N}evertheless, a spatial autocorrelation exists between pixels, reflecting the tendency of neighboring pixels to present similar characteristics. {C}onsidering these aspects, some developments have been initiated to introduce spatial information in the spectral unmixing process, called the spectral–spatial unmixing technique. {T}his chapter aims to provide a review of these developments to the remote sensing community.},
  keywords = {},
  booktitle = {{R}esolving spectral mixtures with applications from ultrafast time-resolved spectroscopy to super-resolution imaging},
  numero = {30},
  pages = {579--611},
  address = {{A}msterdam},
  publisher = {{E}lsevier},
  series = {{D}ata {H}andling in {S}cience and {T}echnology},
  year = {2016},
  DOI = {10.1016/{B}978-0-444-63638-6.00018-8},
  ISBN = {978-0-444-63638-6},
  ISSN = {0922-3487},
  URL = {https://www.documentation.ird.fr/hor/fdi:010070173},
}