PARISS hyperspectral imaging software
performs supervised and un-supervised
spectral classification and creates reference
spectral libraries.
Signals buried in noise are revealed using
spectral waveform cross-correlation (SWCCA)
PARISS® Hyperspectral Imaging
Field-Scanning Software Workflow
PARISS Spectral Imaging Spectroscopy Software Essentials
Programing language: Python.
Spectral classification: Unsupervised and supervised spectral classification. The user controls the number of
revealed classes. Algorithms based on Spectral Waveform Cross-Correlation (SWCCA)
Reference Spectral Libraries (RSL): A libraries of spectral classes that correlate with known objects or conditions.
Classes can be added or removed, named and pseudo-colored by the user
Spectral recognition: Correlates spectra presented by objects in the FOV with library spectra. The user selects
the degree of correlation as a function of a user-selected minimum correlation coefficient (MCC) based on SWCCA.
Spectroscopy functions: Math functions enable % Reflection, %Transmission, Fluorescence, Luminescence…
Spectral plots: Single and multiple in 3D
Camera control: Both the spectrum camera and observed image cameras
Statistics: Display in a histogram or pie-chart format
PARISS SWCCA Extracts Signal From Noise Even
In Non-Linear Conditions
Utilizes proprietary algorithms developed in
house, based on Spectral Waveform Cross
Correlation Analysis (SWCCA)
Linearity independent SWCCA algorithms
accommodate non-linear spectral mixing that
normally occurs in biological samples.
Highly tolerant of low S/N spectra: enables the
generation of robust Reference Spectral Libraries
(RSL) and correlation between sample spectra and
RSL spectra.
Reference Spectral Libraries that truly represent
your samples.
Enables accurate spectral segmentation.
Standardized spectra Spectra acquired with
PARISS can be standardized in absorption, %
transmission/reflection.
Publication ready spectra can be compared with
spectra acquired on any other analytical instrument.
Powerful topographical mapping: spectra from
the FOV that “correlate” with RSL spectra can be
pseudo-colored and “painted” onto a gray-scale
image, with pixel-perfect accuracy.
PARISS Hyperspectral Software Includes:
Logical operators: “equals” and “not equals” at a
user defined threshold. Controls risk of false
positives or negatives.
User created “real life” reference spectral
libraries:
Hyperspectral imaging software includes
spectral topographical mapping: Map the location
in a FOV of all or some target objects.
SWCCA algorithms capture natural variations
in spectral profile that indicate change such as:
pH, ion-concentration, charge, and conformation.
Measure change over time: PARISS can acquire
spectra automatically over a user defined period,
then play the results back as a movie.
Observe raw spectra: all acquisitions can be
exported to third party math or imaging programs.
PARISS® Hyperspectral Imaging Software