QGIS/python/plugins/processing/otb/description/doc/HyperspectralUnmixing.html
2013-08-20 09:22:03 +02:00

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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//ENhttp://www.w3.org/TR/REC-html40/strict.dtd"><html><head><meta name="qrichtext" content="1" /><style type="text/css">p, li { white-space: pre-wrap; }</style></head><body style=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"></style></head><body style=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"><p align="center" style=" margin-top:16px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:x-large; font-weight:600;"><span style=" font-size:x-large;">Hyperspectral data unmixing</span></p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Brief Description</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Estimate abundance maps from an hyperspectral image and a set of endmembers.</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Tags</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Hyperspectral</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Long Description</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">The application applies a linear unmixing algorithm to an hyperspectral data cube. This method supposes that the mixture between materials in the scene is macroscopic and simulate a linear mixing model of spectra.
The Linear Mixing Model (LMM) acknowledges that reflectance spectrum associated with each pixel is a linear combination of pure materials in the recovery area, commonly known as endmembers.Endmembers can be estimated using the VertexComponentAnalysis application.
The application allows to estimate the abundance maps with several algorithms : Unconstrained Least Square (ucls), Fully Constrained Least Square (fcls),Image Space Reconstruction Algorithm (isra) and Non-negative constrained Least Square (ncls) and Minimum Dispersion Constrained Non Negative Matrix Factorization (MDMDNMF).
</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Parameters</span></p><ul><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Input Image Filename (-in): </span>The hyperspectral data cube to unmix</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Output Image (-out): </span>The output abundance map</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Input endmembers (-ie): </span>The endmembers (estimated pure pixels) to use for unmixing. Must be stored as a multispectral image, where each pixel is interpreted as an endmember</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[choice] Unmixing algorithm (-ua): </span>The algorithm to use for unmixing</p><ul><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[group] UCLS: </span>Unconstrained Least Square</p><ul></ul></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[group] FCLS: </span>Fully constrained Least Square</p><ul></ul></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[group] NCLS: </span>Non-negative constrained Least Square</p><ul></ul></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[group] ISRA: </span>Image Space Reconstruction Algorithm</p><ul></ul></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[group] MDMDNMF: </span>Minimum Dispersion Constrained Non Negative Matrix Factorization</p><ul></ul></li></ul></li><br /></ul><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Limitations</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">None</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Authors</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">OTB-Team</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">See also</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">VertexComponentAnalysis</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Example of use</span></p><ul><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><li>Parameters to set value:</li></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><ul><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Input Image Filename: hsi_cube.tif</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Output Image: HyperspectralUnmixing.tif double</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Input endmembers: endmembers.tif</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Unmixing algorithm: ucls</p></li></ul></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><li>Command line to execute:</li></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:'Courier New, courier';">otbcli_HyperspectralUnmixing -in hsi_cube.tif -out HyperspectralUnmixing.tif double -ie endmembers.tif -ua ucls</p></ul></body></html>