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Unmixing (descriptor)

Use the spectral information from pure samples imported as end members to gain information about the objects and display them in the table view using Constrained Spectral Unmixing.



Choose to use constrained spectral unmixing for quantification or classification.


Use one of the following regression methods to compare the end member spectrum to the measurements:

  • None Negative Least Squares

  • Sum To One Least Squares

Scatter correction

  • None

    • No scatter correction applied.

  • Baseline

    • A constant scatter correction is applied.

  • Slope

    • A linear scatter correction is applied.

  • Parabola

    • A quadratic scatter correction is applied.

Expression (Optional)

To include extra expression.


  • Baseline

    • Use the end member as the property and depict the result in the table view.

  • R2

    • Shows the R” value in the table view

  • Expression

    • Shows the expression stated in the “Expression (Optional)” in the table view.


Write in the wavelength range to use. If left empty all wavelengths are included.

End Members (1-10)

Select files containing End members for each pure sample.


Smooth prediction result using median filter kernel

  • None

    • No Smoothing prediction.

  • Low

    • Smoothing using median filter kernel with 5x5 pixel box

  • Medium

    • Smoothing using median filter kernel with 10x10 pixel box

  • High

    • Smoothing using median filter kernel with 15x15 pixel box

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