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Data Analysis and Modelling

Large built-in tool box for advanced analysis and modelling of your data combined with a user-friendly interface that makes it easy and fast to analyse your data.
Breeze features a comprehensive toolbox for advanced hyperspectral data analysis, including machine learning, chemometric methods, comparison based methods, and band math functions.  Seamless Python integration allows users to add custom algorithms. And the support for .ONNX files enables the user to run externally trained custom neural network models. Designed for both experts and beginners, Breeze enhances productivity and speeds up hyperspectral imaging applications.

Classification

Perform image analysis on pixel and object level where you have discrete data (i.e. classes A, B or C).

Quantification

Perform image analysis on pixel and object level where you have continuous variables (e.g. %, mg/l etc) using available methods

Machine learning

Large selection of models that can be manually selected and auto function that proposes the best model based on cross validation.

Available models:
  • Neural network
  • Decision tree
  • Support vector machine
  • Random forest
  • Logistic regression
  • Maximum entropy
  • Poisson regression
  • Linear Regression

Chemometrics

Chemometrics models are powerful and fast tools for analysis, diagnostics and visualisation of your data.

Available models:
  • PLS
  • PLS-DA
  • Hierarchical PLS-DA, 
  • SIMCA, 
  • PCA, 
  • K-means
  • Gaussian mixture mode

Comparison based analysis

Generate your own end member spectra in the software or import existing spectral libraries. Then compare with your hyperspectral data to perform the analysis. Available models: Constrained Spectral unmixing and Spectral angle mapper

Band math

Select from a long list of available band math functions such as Vegetation Indexes, or write your own functions.

Neural network ONNX models

Import and run externally trained neural network models thanks to our support for the .ONNX file format that can be generated using software like Matlab and Pythorch.

Python Interface

Run your own Python code for data processing steps in combination with the built in functions and methods in the software

Breeze features a comprehensive toolbox for advanced hyperspectral data analysis, including machine learning, chemometric methods, comparison based methods, and band math functions.  Seamless Python integration allows users to add custom algorithms. And the support for .ONNX files enables the user to run externally trained custom neural network models. Designed for both experts and beginners, Breeze enhances productivity and speeds up hyperspectral imaging applications.

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