TRT Filter for Impulse Noise Removal

Thresholding and Regularization Techniques for Image Denoising
43 Downloads
Updated 5 Jul 2022

TRT_Filter

Thresholding and Regularization Techniques for Image Denoising

GUI requires MATLAB 2021b

Cite the paper:

Nguyen N. Hien, Dang N.H. Thanh, Ugur Erkan, Joao M.R.S. Tavares. “Image Noise Removal Method Based on Thresholding and Regularization Techniques.” IEEE Access, vol. 10, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 71584–97, doi:10.1109/access.2022.3188315.

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% For the first time you run the app, you need to set up MEX enviroment

% by running the following command:

% install

% A mex file will be generated, usually tv_restore.mexmaci64,

% tv_restore.mexwindow64, etc.

% =============================

% If you want to test the algorithm without GUI, run the below code:

% clc;

% close all;

% I = imread('232038.jpeg');

% [In, Id] = TRTDenoise(I, .7);

% imshow([I, In, Id]);

% If you want to use GUI, run the below code:

TRTapp

Cite As

Nguyen N. Hien, Dang N.H. Thanh, Ugur Erkan, Joao M.R.S. Tavares. “Image Noise Removal Method Based on Thresholding and Regularization Techniques.” IEEE Access, vol. 10, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 71584–97, doi:10.1109/access.2022.3188315.

MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.1

See release notes for this release on GitHub: https://github.com/thanhdnh/TRT_Filter/releases/tag/v1.1

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.