HYPERSPECTRAL IMAGE ANALYSIS

Solo+MIA combines the stand-alone graphical environment of Solo with the Multivariate Image Analysis (MIA) tools from our popular MIA_Toolbox. This combination allows users to apply multivariate analysis tools directly to hyperspectral image data and view the results in image format.

SOLO+MIA WORKS SEEMLESSLY WITH IMAGES:

  • “Automatic image display” technology to recognize and automatically present appropriate model results in image format.
  • Image importing and building functions to make assembly of multivariate images easier.
  • Image specific functions including Maximal Autocorrelation Factors (MAF) and an image-enhanced Cluster analysis.
  • Enables most standard Solo analysis methods to work with images.

INCLUDES ALL OF THESE FEATURES AND MORE:

  • Data Exploration and Pattern Recognition (Principal Components Analysis, Parallel Factor Analysis)
  • Regression Modeling (Partial Least Squares, Principal Components Regression, Multiple Linear Regression…)
  • Classification (SIMCA, PLS Discriminant Analysis, Cluster Analysis with Dendograms…)
  • Self-modeling Curve Resolution, Pure Variable Methods (Multivariate Curve Resolution, Purity (compare to SIMPLSMA))
  • Instrument Standardization (Piece-wise Direct, Generalized Least Squares Preprocessing…)
  • Advanced Graphical Data Set Editing and Visualization Tools
  • Advanced Customizable Order-Specific Preprocessing (Centering, Scaling, Smoothing, Derivatizing…)

SYSTEM REQUIREMENTS

MAC OSX (Intel), Linux, Windows XP, VISTA, Win7, Win8, or Win10. 250 MB of disk space and a recommended minimum of 500 MB of RAM (more may be necessary for some data) and a minimum of 16 bit color graphics are also required.

PRODUCT SUPPORT

Eigenvector Research offers user support for Solo+MIA . Questions are almost always answered within 24 hours (and usually much less). Updates and bug fixes will be available for users to download from our web site. For information on other support options.

About Eigenvector

RESOURCES

The View from Eigenvector
White Papers
Data Sets
EigenGuides
Documentation WIKI
MATLAB User Area

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