Repository for Scale-recurrent Network for Deep Image Deblurring
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Updated
Oct 8, 2018 - Python
Repository for Scale-recurrent Network for Deep Image Deblurring
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
Class-Specific Image Deblurring
Our method utilizes convolution and probabilistic diffusion models to efficiently perform the image deblurring task.
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.
SPL Paper Codes
Image deblurring using low rank approximation
Image processing filters and applications
EEL2010 Signals and Systems Course Programming Assignment. This code removes noise (denoise) and then sharpen (deblur) the signal.
When photographing a light source with a smartphone camera, light smudging often occurs. Our model contributes to improving the image quality degraded by the spread of light around the light source.
Blind and non-blind Richardson-lucy deconvolution using pytorch
Image Deblurring using Generative Adversarial Networks
A deblurring task confronted by a CNN, a RNN and a SUnet.
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