Skip to content

chintan1995/Image-Denoising-using-Deep-Learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

NOTE: In case you are not able to view the ipynb files on github, then paste its link on nbviewer, https://nbviewer.jupyter.org/

Image-Denoising-using-Deep-Learning

In this repo I have implemented three different deep learning architectures for image denoising,
REDNet; https://arxiv.org/pdf/1606.08921.pdf
Multi-level Wavelet CNN (MWCNN); https://arxiv.org/pdf/1805.07071.pdf
PRIDNet; https://arxiv.org/pdf/1908.00273.pdf

I found that PRIDNet was giving the best results as compared to the other two, giving me the best PSNR and SSIM scores along with best visualizations which were very close to the ground truth images.

Screenshot

PRIDNet Results

Screenshot Screenshot Screenshot Notice the level of detail in the eye ball.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published