Hyperspectral image analysis add-on for PLS_Toolbox


  • Enables PLS_Toolbox functions and graphical interfaces to work with hyperspectral images
  • Allows image analysis using PCA, curve resolution, linear and nonlinear regression and classification, and more
  • Includes image-specific analysis tools such as windowed factor analysis and MAF
  • Imports from numerous scientific instrumentation sources and performs hyperspectral data fusion
  • Integrates flexible particle finding and texture analysis tools directly with multivariate analysis tools
  • Enables easy follow-on analyses via direct integration with ImageJ (NIH)


With MIA_Toolbox, hyperspectral images from microscopy to remote sensing can be easily analyzed using the familiar PLS_Toolbox tools. Load, manipulate, and analyze multivariate images in the Analysis graphical interface and employ high-level command-line functions. Analyze images using a wide array of tools including principal component analysis, multivariate curve resolution, and linear and nonlinear regression and classification methods (SVM, PLS, CLS, PLSDA, LWR, SIMCA, K-Means clustering, and more). Quickly identify ROIs and spectral ranges of interest in an interactive point-and-click environment. 

MIA_Toolbox adds tools designed to take advantage of the spatial relationship inherent in a multivariate image including particle analysis, texture analysis, evolving window factor analysis, and maximal autocorrelative factors (MAF). These are available from the MATLAB command line and from flexible graphical interfaces. Other tools include the Image Manager, which allows image importing, organization, and editing (cropping, augmenting, rotating, etc.), and TrendTool, which provides quick univariate investigative analyses (peak location, area, ratios). 

MIA_Toolbox provides integrated access to multivariate image importing and preprocessing tools. Importing tools automatically appear in the PLS_Toolbox importing menus and are accessible from simple command-line functions. Preprocessing methods including flat-fielding, windowed smoothing, binary mask manipulations (erode/dilate), and spike filtering are automatically listed along with standard preprocessing methods while analyzing data.

Eigenvector Research, Inc.

3905 W Eaglerock Dr
Wenatchee, WA 98801
Tel: 509-662-9213
Fax: 509-662-9214

Required Products


  • Macintosh
  • UNIX
  • Windows


  • E-mail
  • Fax
  • Training

Product Type

  • Data Analysis Tools


  • Data Analysis and Statistics
  • Image Processing and Computer Vision
  • Optics


  • Aerospace and Defense
  • Biotech and Pharmaceutical
  • Earth, Ocean, and Atmospheric Sciences
  • Semiconductor