Added the registration module MERIT.
The MERIT (MeVis Image Registration Toolkit) module is a software framework for image registration. It is particularly aimed at the rapid prototyping of registration methods often required in everyday work with MeVisLab. Among its core features are:
2-D/3-D affine-linear image transformations (translation, rigid, similarity, rigid+scale, affine) with customizable component orders.
Newton-type optimization (and approximation thereof) with line-searching (linear or Armijo's rule).
Multi-resolution image pyramids with custom downsampling, stop levels, and number of levels.
Inherent pre-registration initialization schemes (e.g., initial matching of centers of gravity).
Five common image similarity measures (SSD, NCC, NMI, LCC, NGF).
Nearest neighbor, cubic, Lanczos, and linear image interpolation methods.
Multi-threading support using OpenMP processor threads.
Robust convergence criteria, e.g. Gill-Murray-Wright, for a unified convergence behavior of all algorithms.
Entirely graphical usage through a consistent user interface.
Error curve output, mask image support, plugin methods, and much more.
The python-based 2D plotting library Matplotlib ( http://matplotlib.sourceforge.net/) has been integrated into MeVisLab.
Qt4 backend has been ported to PythonQt/MeVisLab.
MatplotlibCanvas MDL control allows to embedd plots in MeVisLab UIs.
See MatplotlibMDLExample for an example usage.
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