Image restoration models that can be used as a baseline (last updated 10/1/21)
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Updated
Oct 1, 2021 - Python
Image restoration models that can be used as a baseline (last updated 10/1/21)
⚡Accelerated nerfstudio implementation of 😈 BAD-NeRF (CVPR 2023). Train a scene from blurry images in minutes!
Repository for Scale-recurrent Network for Deep Image Deblurring
Digital image processing C++ for algo. and Matlab for display.
A Deep Learning model for denoising - deblurring an image.
Improved weed segmentation in UAV imagery of sorghum fields with a combined deblurring segmentation model
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
This software is a collection of algorithms for noise estimation, denoising, and deblurring developed by the Signal and Image Restoration group of the Tampere.
Implementation of defiltering techniques for blurry and noisy images
Implementation of Tracking by Deblatting
Class-Specific Image Deblurring
Computational DeFogging framework building off of previous research. U of U Summer Program for Undergraduate Research (SPUR) 2024.
This repository is part of an ongoing personal project to understand and improve video/image restoration and processing.
Position-Dependent Richardson-Lucy deconvolution
This is an improved version of the deblurring of faces. It shows about 5% increase in SSIM metric in comparison with the original methods. Tweaked the existing dehazing algorithms to work for deblurring.
“Disparitybased space-variant image deblurring,” Signal Processing: Image Communication, vol. 28, no. 7, pp. 792–808, 2013.
Our method utilizes convolution and probabilistic diffusion models to efficiently perform the image deblurring task.
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