Python code implementing five reverse filtering (or defiltering) schemes for noisy image deblurring described in the following paper.
The code depends on a few common Python libraries (NumPy, ...). Install them via pip
and the provided requirements.txt
file.
For example
$ python -m venv bbdeblur_venv
$ ./bbdeblur_venv/Scripts/activate
$ pip install -r requirements.txt
One possibility is to execute the scripts in the sub-directory src
$ cd src
$ python test_color.py
Another possibility is to use the Python notebook, provided in the sub-directory notebooks
. The notebook works on Google Colab (with the default installation).
See also the original (and more complete) MATLAB implementation in this repo.
Link to the paper where the methods were introduced. The corresponding bibtex entry is
@article{Belyaev2022,
title = {Black-box image deblurring and defiltering},
author = {Belyaev, Alexander G. and Fayolle, Pierre-Alain},
journal = {Signal Processing: Image Communication},
pages = {116833},
year = {2022},
issn = {0923-5965},
doi = {https://doi.org/10.1016/j.image.2022.116833},
url = {https://www.sciencedirect.com/science/article/pii/S0923596522001242},
keywords = {Deblurring, Defiltering, Reverse filtering},
}