IRCNN
Image Restoration Library
This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods.
Learning Deep CNN Denoiser Prior for Image Restoration (CVPR, 2017) (Matlab)
602 stars
33 watching
172 forks
Language: MATLAB
last commit: almost 5 years agoLinked from 2 awesome lists
color-demosaickingdeep-modelimage-deblurringimage-denoisingimage-inpaintingimage-restorationsingle-image-super-resolution
uhub/awesome-matlabRelated projects:
| Repository | Description | Stars |
|---|---|---|
| cszn/srmd | Develops a single convolutional network to handle various image degradations with improved scalability and efficiency | 427 |
 subeeshvasu/2018_subeesh_nbd_cvpr | Provides results and tools for image deblurring using CNNs to handle kernel uncertainty | 5 |
 swz30/mprnet | A deep learning model designed to progressively restore degraded images by iteratively refining the degradation and its representation in the image | 1,197 |
 csjcai/dbcpenet | Deblurring technique developed using machine learning and signal processing algorithms to restore images from blurry conditions. | 20 |
| cszn/dpsr | A deep learning-based method to improve image quality by reducing blur effects | 839 |
 cszcwu/nrknet | A software framework for single image deblurring using recursive kernels | 14 |
 lingyanruan/lakdnet | An image deblurring model that revisits the use of convolutional neural networks to improve efficiency and performance compared to transformers. | 102 |
 algolzw/daclip-uir | This project controls vision-language models to restore degraded images in various environments and conditions. | 673 |
 ysnan/vem-nbd | Provides pre-trained models and benchmark results for noise-blind image deblurring, allowing developers to test and compare different approaches. | 14 |
| cszn/bsrgan | A deep learning-based approach to super-resolution of degraded images. | 1,222 |
 hyeongseokson1/cnn_deconvolution | An implementation of a CNN-based method for non-blind deconvolution using Wiener filtering as a pre-processing step. | 22 |
 minyuanye/siun | This project develops a deep learning-based image deblurring algorithm using iterative upsampling network architecture | 164 |
 codeslake/ifan | Implementation of an algorithm for single image deblurring in images with defocus blur | 228 |
 xlearning-scu/2022-cvpr-airnet | Restores degraded images by combining multiple tasks of dehazing, denoising and deraining in a single framework | 176 |
| hyeongseokson1/kpac | An implementation of a deep learning model for deblurring images affected by defocus. | 58 |