semvec/pypi-packages huggingface dataset:
imreg 2025.1.1
FFT based image registration
License: BSD
Requires Python: >=3.10

FFT based image registration
============================

Imreg is a Python library that implements an FFT-based technique for
translation, rotation and scale-invariant image registration [1].

:Author: `Christoph Gohlke <https://www.cgohlke.com>`_
:License: BSD 3-Clause
:Version: 2025.1.1

Quickstart
----------

Install the imreg package and all dependencies from the
`Python Package Index <https://pypi.org/project/imreg/>`_::

    python -m pip install -U imreg

See `Examples`_ for using the programming interface.

Source code and support are available on
`GitHub <https://github.com/cgohlke/imreg>`_.

Requirements
------------

This revision was tested with the following requirements and dependencies
(other versions may work):

- `CPython <https://www.python.org>`_ 3.10.11, 3.11.9, 3.12.8, 3.13.1 64-bit
- `NumPy <https://pypi.org/project/numpy/>`_ 2.1.3
- `Scipy <https://pypi.org/project/scipy>`_ 1.14.1
- `Matplotlib 3.10.0 <https://pypi.org/project/matplotlib>`_
  (optional for plotting)

Revisions
---------

2025.1.1

- Drop support for Python 3.9, support Python 3.13.

2024.5.24

- Support NumPy 2.
- Fix docstring examples not correctly rendered on GitHub.

2024.1.2

- Add type hints.
- Drop support for Python 3.8 and numpy < 1.23 (NEP29).

2022.9.27

- Fix scipy.ndimage DeprecationWarning.

Notes
-----

Imreg is no longer being actively developed.

This implementation is mainly for educational purposes.

An improved version is being developed at https://github.com/matejak/imreg_dft.

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.

Examples
--------

>>> im0 = imread('t400')
>>> im1 = imread('Tr19s1.3')
>>> im2, scale, angle, (t0, t1) = similarity(im0, im1)
>>> imshow(im0, im1, im2)

>>> im0 = imread('t350380ori')
>>> im1 = imread('t350380shf')
>>> t0, t1 = translation(im0, im1)
>>> t0, t1
(20, 50)