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.