MIA_Toolbox

Hyperspectral image analysis add-on for PLS_Toolbox

Highlights

  • 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 EWFA, MAF, and an image-enhanced cluster analysis
  • Texture-analysis functions encode spatial information for use in pattern recognition or regression analysis
  • Edge detection, image erosion, and morphing tools
  • Wide array of file importers

Description

mia-toolbox

MIA_Toolbox for Multivariate Image Analysis expands the already comprehensive PLS_Toolbox functionality with many image-specific functions and builds on PLS_Toolbox interfaces to make analysis of multivariate images simple and intuitive.

With MIA_Toolbox, hyperspectral images from microscopy to remote sensing can be easily analyzed using your familiar PLS_Toolbox tools. Load, manipulate, and analyze multivariate images in the analysis graphical interface. Enjoy higher-level command-line functions. Perform principal components analysis, Multivariate Curve Resolution (ALS and Purity), SIMCA and PLSDA classification, k-means clustering, and even PLS or PCR regression. MIA_Toolbox also adds functions designed to take advantage of the special “spatial” relationship inherent in a multivariate image, including functions like evolving window factor analysis and maximal autocorrelative factors, and a suite of texture functions.

eigenvector-logo

Eigenvector Research, Inc.

196 Hyacinth Road
Manson, WA 98831
UNITED STATES
Tel: 509-662-9213
bmw@eigenvector.com
https://eigenvector.com/

Required Products

Platforms

  • Linux
  • Macintosh
  • UNIX
  • Windows

Support

  • Consulting
  • E-mail
  • Training

Product Type

  • Data Analysis Tools

Tasks

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

Industries

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