Welcome to imreg_dft’s documentation!¶
General overview¶
imreg_dft
implements DFT[*] -based technique for translation, rotation and scale-invariant image registration.
In plain language, imreg_dft
implements means of calculating 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].
[*] | DFT stands for Discrete Fourier Transform. Usually the acronym FFT (Fast Fourier Transform) is used in this context, but this is incorrect. DFT is the name of the operation, whereas FFT is just one of possible algorithms that can be used to calculate it. |
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Requirements¶
See the requirements.txt
file in the project’s root for the exact specification.
Generally, you will need numpy
and scipy
for the core algorithm functionality.
Optionally, you may need:
pillow
for loading data from image files,matplotlib
for displaying image output,pyfftw
for better performance.
Quickstart¶
Head for the corresponding section of the documentation. Note that you can 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 runmake 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¶
[1] | 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 |
[2] | 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. |
[3] | Image Registration Using Adaptive Polar Transform. R Matungka, YF Zheng, RL Ewing. IEEE Transactions on Image Processing, 18(10), 2009. |