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.

Feature	Epina ImageLab Basic	Epina ImageLab Extended	Epina ImageLab Database	Epina ImageLab Enterprise Edition	More Infos
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 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 information
Atmospheric Compensation Use this tool to remove unwanted CO2 or H2O bands from the spectra.
Multiprocessing Epina ImageLab supports multiprocessing to speed up the calculations.
Chartbook 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