Image registration procedure based on discrete Fouriertransform (DFT)
Project description
imreg_dft implements DFT[*] -based technique for translation, rotation and scale-invariant image registration.
In plain language, imreg_dft implements means of guessing translation, rotation and scale variation between two images. It doesn’t work with those images directly, but it works with their spectrum, using the log-polar transformation. The algorithm is described in [1] and possibly also in [2] and [3].
- Authors:
- Organization:
Laboratory for Fluorescence Dynamics, University of California, Irvine
Brno University of Technology, Brno, Czech Republic
- Copyright:
2011-2014, Christoph Gohlke
2014-2015, Matěj Týč
Requirements
See the requirements.txt file in the project’s root for the exact specification. Generally, you will need numpy and scipy for the algorithm functionality and matplotlib for plotting.
Quickstart
Read the docs, the full-blown quickstart is there. Disregard this section if you actually are reading the docs (and not the project’s webpage, where this text also appears).
Or even better, generate the documentation yourself!
Install the package by running python setup.py install in the project root.
Install packages that are required for the documentation to compile (see the requirements_docs.txt file.
Go to the doc directory and run make html there. The documentation should appear in the _build subfolder, so you may open _build/html/index.html with your web browser to see it.
Notes
The API and algorithms are quite good, but help is appreciated. imreg_dft uses semantic versioning, so backward compatibility of any kind will not break across versions with the same major version number.
imreg_dft is based on the code by Christoph Gohlke.
References
An FFT-based technique for translation, rotation and scale-invariant image registration. BS Reddy, BN Chatterji. IEEE Transactions on Image Processing, 5, 1266-1271, 1996
An IDL/ENVI implementation of the FFT-based algorithm for automatic image registration. H Xiea, N Hicksa, GR Kellera, H Huangb, V Kreinovich. Computers & Geosciences, 29, 1045-1055, 2003.
Image Registration Using Adaptive Polar Transform. R Matungka, YF Zheng, RL Ewing. IEEE Transactions on Image Processing, 18(10), 2009.