Skip to main content

A port of the Dual-Tree Complex Wavelet Transform MATLAB toolbox.

Project description

This library provides support for computing 1D, 2D and 3D dual-tree complex wavelet transforms and their inverse in Python. Full documentation is available online. Coverage License Latest Version Downloads


The easiest way to install dtcwt is via easy_install or pip:

$ pip install dtcwt

If you want to check out the latest in-development version, look at the project’s GitHub page. Once checked out, installation is based on setuptools and follows the usual conventions for a Python project:

$ python install

(Although the develop command may be more useful if you intend to perform any significant modification to the library.) A test suite is provided so that you may verify the code works on your system:

$ python nosetests

This will also write test-coverage information to the cover/ directory.

Further documentation

There is more documentation available online and you can build your own copy via the Sphinx documentation system:

$ python build_sphinx

Compiled documentation may be found in build/docs/html/.


Based on the Dual-Tree Complex Wavelet Transform Pack for MATLAB by Nick Kingsbury, Cambridge University. The original README can be found in ORIGINAL_README.txt. This file outlines the conditions of use of the original MATLAB toolbox.



  • Verified the highpass re-sampling routines in dtcwt.sampling against the existing MATLAB implementation.
  • Added experimental image registration routines.
  • Re-organised documentation.


  • Fixed regression from 0.7 where backend_opencl.dtwavexfm2 would return None, None, None.


  • Fix a memory leak in OpenCL implementation where transform results were never de-allocated.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
dtcwt-0.8.0.tar.gz (3.1 MB) Copy SHA256 hash SHA256 Source None Jan 30, 2014

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page