Comparison of Software Versions

Epina ImageLab is available in three different versions: the Basic Edition provides all important imaging tools and a basic set of mathematical methods. The Extended Edition additionally offers a script engine which allows you to automate everyday tasks in Epina ImageLab. Further it provides additional high-end chemometric models and it supports 64-bit operating systems, which removes the limitation of the maximum datafile size. The Database Extensions add database functionality to your Epina ImageLab installation. All three packages together are also available as a complete package (called "Enterprise Edition").

The following table gives a quick overview of the features which are available in the various versions of Epina ImageLab.

Epina ImageLab
Epina ImageLab
Epina ImageLab
Epina ImageLab
User Interface in Different Languages
currently English and German are supported
Automatic Updates
Epina ImageLab checks whether a newer version is
available and downloads the new version
from the Epina ImageLab server.
3D Display of Images
Rotatable 3D surfaces indicating the
intensity distribution in 3D
Image Stack
The image stack allows to blend
up to eight different images.
Bookmarks allow to remember spectra at
particular positions and to quickly navigate
to these locations.
Detection of Suspicious Pixels
Suspicious pixels are pixels with
no signal, noise only, or uncorrelated ones.
Path Length Measurement
You can measure the length of an
irregular path or the area of a closed path.
Principal Component Analysis
PCA score plots and the cluster analysis
of the loadings will uncover hidden
information your data contains.
Maximum Noise Fraction Transform
MNF allows to detect and reduce noise
in images.
Vertex Component Analysis
The best method to detect pure
components in your data.
Similarity Maps
Detect spectroscopically similar
regions in your image.
Cluster Analysis
Hierarchical cluster analysis resulting
in a dendrogram which can be used
to assign classes.
K-Means Clustering
Both standard k-means and
fuzzy-c-means clustering.
PLS Discriminant Analysis
Create classifiers to detect regions of
particular interest in your images.
Image Preprocessing
All kinds of basic procedures (e.g. spatial
and spectral filtering, scaling of the data,
mathematical transformations, etc.
Baseline Correction
Three methods are available: polynomials,
penalized splines and the Lieber algorithm
Spectral Descriptors
Spectral descriptors form the basis to fight
the curse of dimensionality and to increase
the selectivity of chemeometric models.
Derivative Spectra
Smoothed 1st and 2nd derivatives
Spike Detection and Removal
The detection and removal of spikes is especially
important in Raman imaging which is prone
to spikes originating from cosmic rays.
Smoothing of Spectra
Moving average, weighted average,
polynomial smoothing, moving median
Fourier Analysis of Spectra
Utilize the power of FFT (Fast Fourier Transform)
to analyse your spectra.
Chemical Maps
You apply mathematical transformations to
your data to create images showing selective
Atmospheric Compensation
Use this tool to remove unwanted
CO2 or H2O bands from the spectra.
Epina ImageLab supports multiprocessing to speed up
the calculations.
Display calculated diagrams in up to 8 charts.
4D Data Model
The imaging data are stored in four dimensions:
spatial [X,Y], spectral and time (or depth)
Pixel Attribute Editor
A tool to assign attributes to individual pixels.
Particle Detection
A toolset for the automatic detection of particles.
Spectral Collections
A useful tool for paying special attention to
inidividual pixels of an image
64-bit Architecture
The size of the data cube is no longer limited to
2 GByte (which is typical for 32 bit systems)
but is limited by the locally installed RAM only
Epina ImageLab Script Automation
A flexible and powerful script language
allows to automate your everyday tasks
User-defined Action Buttons
Allows you to define buttons which are assigned
to specific scripts
KNN Classifiers
KNN classifiers comprise high-performing
non-linear classification methods.
Random Forest Classifiers
Use the powerful random forest
method to create classifiers.
Multisensor Support
You can combine up to four spectroscopic
methods for the same dataset
FFT-based Spectral Filtering
Design any kind of filter to remove
artifacts from your spectra.
User Definable Spectral Databases
Collect your own spectral data and
compile them into a searchable database.
Support of Third-Party Databases
Obtain spectral databases from third parties
and utilize these databases in Epina ImageLab.
Library Search
A powerful library search engine will support
you in identifying unknown spectra