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MathImag's Projects

2010-laa-numerical-cs icon 2010-laa-numerical-cs

C. Dossal, G. Peyré, J. Fadili. A Numerical Exploration of Compressed Sampling Recovery. Linear Algebra and Applications, 432(7), pp. 1663–1679, 2010.

2011-tip-tv-projection icon 2011-tip-tv-projection

J. Fadili, G. Peyré. Total Variation Projection with First Order Schemes. IEEE Transactions on Image Processing, 20(3), pp. 657–669, 2011.

2012-siims-nl-ac icon 2012-siims-nl-ac

M. Jung, G. Peyré, L. D. Cohen. Nonlocal Active Contours. SIAM Journal on Imaging Sciences, 5(3), pp. 1022–1054, 2012.

2014-siims-sugar icon 2014-siims-sugar

C. Deledalle, S. Vaiter, G. Peyré, J. Fadili. Stein Unbiased GrAdient estimator of the Risk (SUGAR) for multiple parameter selection. SIAM Journal on Imaging Sciences, 7(4), pp. 2448–2487, 2014.

2019-tci-onlinepnp icon 2019-tci-onlinepnp

The code for "An online plug-and-play algorithm for regularized image reconstruction", IEEE TCI, 2019.

airtoolsii icon airtoolsii

The AIR Tools II toolbox for MATLAB accompanies the publication "AIR Tools II: algebraic iterative reconstruction methods, improved implementation", Hansen, P. C. & Jørgensen, J. S. Numer Algor (2017).

awesome-matlab icon awesome-matlab

A curated list of awesome MATLAB toolboxes, applications, software and resources.

bm3d icon bm3d

BM3D algorithm for image denoising implemented by Matlab

coco icon coco

This is the Python code for running the experiments given in https://arxiv.org/pdf/1902.09025.pdf, "Single-forward-step projective splitting: Exploiting cocoercivity", Patrick R. Johnstone and Jonathan Eckstein. arXiv preprint arXiv:1902.09025 (2019).

coupled_tgv_recon icon coupled_tgv_recon

Code for coupled TGV regularization of multi-spectral/multi-modal inverse problems

ddpg icon ddpg

Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned Guidance cvpr2014

deblur icon deblur

Image Deblurring with Blurred/Noisy Image Pairs. Yuan et al. 2007.

deepred icon deepred

DeepRED: Deep Image Prior Powered by RED

fast-non-local-means-and-asymptotic-non-local-means icon fast-non-local-means-and-asymptotic-non-local-means

Non-Local means denoising (NLM) algorithm is a milestone algorithm in the field of image processing. The proposal of NLM has opened up the non-local method which has a deep influence. This paper performed a revisit for NLM from two aspects as follows: 1. To alleviate the high computational complexity problem of NLM, a fast algorithm was constructed, which was based on cross-correlation and fast Fourier transform; 2. NLM always blur structures and textures during the noise removal, especially in the case of strong noise. To solve this problem, an Asymptotic Non-Local Means image denoising algorithm is put forward, which uses the property of noise variance to control the filtering parameters. Numerical experiments illustrate that the fast algorithm is 27 times faster than classical implementation with standard parameter configuration, and the ANLM uniformly outperforms classical NLM, in terms of both PSNR and visual effects.

fasthdfilter icon fasthdfilter

P. Nair, and K. N. Chaudhury, "Fast High-Dimensional Bilateral and Non-local Means Filtering," , IEEE Transactions on Image Processing, 28(3), pp.1470-1481.

fastnonlocaldenoising icon fastnonlocaldenoising

. S. Ghosh and K. N. Chaudhury, “Fast separable non-local means,” Journal of Electronic Imaging, vol. 25, no. 2, pp. 023026: 1- 14, 2016.

fima icon fima

On the Convergence of Learning-based Iterative Methods for Nonconvex Inverse Problems (TPAMI 2019)

forbes icon forbes

Generic and efficient MATLAB solver for nonsmooth optimization problems

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