Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
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Updated
Oct 9, 2021 - MATLAB
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
Learning Deep CNN Denoiser Prior for Image Restoration (CVPR, 2017) (Matlab)
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising (TIP, 2018)
Matlab code for our IEEE Trans. on Image Processing paper "NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising"
This repository contains lecture notes and codes for the course "Computational Methods for Data Science"
Image Denoising Codes using STROLLR learning, the Matlab implementation of the paper in ICASSP2017
Image deblocking method using structural sparse representation and quantization constraint
The wavelet transform and its applications in image denoising
This is a companion software for the submission: "Higher-Order Total Directional Variation: Imaging Applications" by Simone Parisotto , Jan Lellmann, Simon Masnou, and Carola-Bibiane Schönlieb. SIAM J. Imaging Sci., 13(4), 2063–2104. (42 pages)
Improving Biometric Quality of Noisy Face Images
Non Local Means Filter for Image Denoising in CUDA
Signal and image denoising using quantum adaptive transformation.
Iterative shrinkage / thresholding algorithms (ISTAs) for linear inverse problems
An implementation of the the paper "Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications" by David Tschumperle and Rachid Deriche
Contains crude computer vision techniques with less emphasis on Deep learning
This matlab code is the implementation of the following paper: Image smoothing via truncated total variation
Diffusion based method for impulse noise removal using residual feedback
Denoising by Quantum Interactive Patches
This repository contains code for the project on "Video Denoising using Low Rank Matrix Completion" completed as a part of the course CS 754 (Advanced Image Processing) at IIT Bombay during the Spring semester of 2022 under Prof. Ajit Rajwade.
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