ACT
Adaptive Curvelet Thresholding for Filtering of Additive Stationary White/Colored Gaussian Noise
This package contains the denoising filter
for additive stationary
white/colored(a.k.a. correlated) Gaussian noise based on the adaptive
curvelet thresholding (ACT) method presented in:
N. Eslahi and A. Aghagolzadeh, "Compressive Sensing Image Restoration Using Adaptive Curvelet Thresholding and Nonlocal sparse Regularization", IEEE Trans. Image Process., vol.25, no.7, pp. 3126-3140, Jul. 2016 https://doi.org/10.1109/TIP.2016.2562563
Author: Nasser Eslahi (Tampere University, Finland)
Contents
The ACT package includes:
ACT_filter.m
the denoising filter based on ACT
demo_denoising.m
a demo code for denoising of additive stationary Gaussian noise
./DCuT/fdct_wrapping.m
forward discrete curvelet transform
./DCuT/ifdct_wrapping.m
inverse/backward discrete curvelet transform
./Test_Images
some images for testing the denoising performance
For a detailed information on each function, please check its corresponding syntax, e.g.,
doc ACT_filter
Visualization of some random tests
demo_denoising.mp4
Disclaimer
Copyright (c) 2006-2022 All rights reserved.
This work should be used for nonprofit purposes and non-commercial use only, see LICENSE
.
Feedback
If you have any comment, suggestion, or question, please do contact
Nasser Eslahi
nasser.eslahi@tuni.fi
nasser.eslahi@gmail.com
Citar como
Nasser Eslahi (2024). ACT (https://github.com/NEslahi/ACT), GitHub. Recuperado .
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1.0.0 |
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