Search Results for author: Raja Giryes

Found 93 papers, 44 papers with code

Membership Inference Attack Using Self Influence Functions

1 code implementation26 May 2022 Gilad Cohen, Raja Giryes

Member inference (MI) attacks aim to determine if a specific data sample was used to train a machine learning model.

Inference Attack Membership Inference Attack

Stress-Testing LiDAR Registration

1 code implementation16 Apr 2022 Amnon Drory, Shai Avidan, Raja Giryes

The standard benchmark for this setting, KITTI-10m, has essentially been saturated by recent algorithms: many of them achieve near-perfect recall.

Autonomous Driving Point Cloud Registration

Denoiser-based projections for 2-D super-resolution multi-reference alignment

1 code implementation10 Apr 2022 Jonathan Shani, Raja Giryes, Tamir Bendory

We study the 2-D super-resolution multi-reference alignment (SR-MRA) problem: estimating an image from its down-sampled, circularly-translated, and noisy copies.


Generative Adversarial Networks

no code implementations1 Mar 2022 Gilad Cohen, Raja Giryes

Generative Adversarial Networks (GANs) are very popular frameworks for generating high-quality data, and are immensely used in both the academia and industry in many domains.

Computer Vision Data Augmentation +1

SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation

1 code implementation31 Jan 2022 Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or

Neural implicit fields are quickly emerging as an attractive representation for learning based techniques.

3D Shape Modeling

Extending the Vocabulary of Fictional Languages using Neural Networks

no code implementations18 Jan 2022 Thomas Zacharias, Ashutosh Taklikar, Raja Giryes

Fictional languages have become increasingly popular over the recent years appearing in novels, movies, TV shows, comics, and video games.

Machine Translation Style Transfer +1

NeuralMLS: Geometry-Aware Control Point Deformation

1 code implementation5 Jan 2022 Meitar Shechter, Rana Hanocka, Gal Metzer, Raja Giryes, Daniel Cohen-Or

In this work, we opt to learn the weighting function, by training a neural network on the control points from a single input shape, and exploit the innate smoothness of neural networks.

Video Reconstruction from a Single Motion Blurred Image using Learned Dynamic Phase Coding

no code implementations28 Dec 2021 Erez Yosef, Shay Elmalem, Raja Giryes

Video reconstruction from a single motion-blurred image is a challenging problem, which can enhance existing cameras' capabilities.

Video Reconstruction

Unsupervised Domain Generalization by Learning a Bridge Across Domains

1 code implementation CVPR 2022 Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogerio Feris, Leonid Karlinsky

The ability to generalize learned representations across significantly different visual domains, such as between real photos, clipart, paintings, and sketches, is a fundamental capacity of the human visual system.

Domain Generalization Self-Supervised Learning

Mesh Draping: Parametrization-Free Neural Mesh Transfer

no code implementations11 Oct 2021 Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or

The method drapes the source mesh over the target geometry and at the same time seeks to preserve the carefully designed characteristics of the source mesh.

DeepBBS: Deep Best Buddies for Point Cloud Registration

1 code implementation6 Oct 2021 Itan Hezroni, Amnon Drory, Raja Giryes, Shai Avidan

The Best Buddies criterion is a strong indication for correct matches that, in turn, leads to accurate registration.

Point Cloud Registration

Simple Post-Training Robustness Using Test Time Augmentations and Random Forest

2 code implementations16 Sep 2021 Gilad Cohen, Raja Giryes

A leading defense against such attacks is adversarial training, a technique in which a DNN is trained to be robust to adversarial attacks by introducing adversarial noise to its input.

Adversarial Robustness

FLEX: Extrinsic Parameter-free Multi-view 3D Human Motion Reconstruction

1 code implementation5 May 2021 Brian Gordon, Sigal Raab, Guy Azov, Raja Giryes, Daniel Cohen-Or

We compare our model to state-of-the-art methods that are not ep-free and show that in the absence of camera parameters, we outperform them by a large margin while obtaining comparable results when camera parameters are available.

3D Human Pose Estimation

Orienting Point Clouds with Dipole Propagation

1 code implementation4 May 2021 Gal Metzer, Rana Hanocka, Denis Zorin, Raja Giryes, Daniele Panozzo, Daniel Cohen-Or

In the global phase, we propagate the orientation across all coherent patches using a dipole propagation.

SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization

no code implementations NeurIPS 2021 Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or

Multilayer-perceptrons (MLP) are known to struggle with learning functions of high-frequencies, and in particular cases with wide frequency bands.

Representation Learning

Multiplicative Reweighting for Robust Neural Network Optimization

1 code implementation24 Feb 2021 Noga Bar, Tomer Koren, Raja Giryes

Yet, their performance degrades in the presence of noisy labels at train time.

Adversarial Robustness

Image Restoration by Deep Projected GSURE

no code implementations4 Feb 2021 Shady Abu-Hussein, Tom Tirer, Se Young Chun, Yonina C. Eldar, Raja Giryes

In the first one, where no explicit prior is used, we show that the proposed approach outperforms other internal learning methods, such as DIP.

Deblurring Image Restoration +1

Separable Joint Blind Deconvolution and Demixing

no code implementations4 Feb 2021 Dana Weitzner, Raja Giryes

Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions.

ISP Distillation

no code implementations25 Jan 2021 Eli Schwartz, Alex Bronstein, Raja Giryes

We then train a model that is applied directly to the RAW data by using knowledge distillation such that the model predictions for RAW images will be aligned with the predictions of an off-the-shelf pre-trained model for processed RGB images.

Knowledge Distillation Object Recognition

A Spectral Perspective of Neural Networks Robustness to Label Noise

no code implementations1 Jan 2021 Oshrat Bar, Amnon Drory, Raja Giryes

Deep networks usually require a massive amount of labeled data for their training.

GMM-Based Generative Adversarial Encoder Learning

no code implementations8 Dec 2020 Yuri Feigin, Hedva Spitzer, Raja Giryes

We model the output of the encoder latent space via a GMM, which leads to both good clustering using this latent space and improved image generation by the GAN.

Image Generation

Best Buddies Registration for Point Clouds

1 code implementation5 Oct 2020 Amnon Drory, Tal Shomer, Shai Avidan, Raja Giryes

We propose new, and robust, loss functions for the point cloud registration problem.

Point Cloud Registration Template Matching

Kernel-Based Smoothness Analysis of Residual Networks

no code implementations21 Sep 2020 Tom Tirer, Joan Bruna, Raja Giryes

A major factor in the success of deep neural networks is the use of sophisticated architectures rather than the classical multilayer perceptron (MLP).

Deep Sparse Light Field Refocusing

1 code implementation5 Sep 2020 Shachar Ben Dayan, David Mendlovic, Raja Giryes

Light field photography enables to record 4D images, containing angular information alongside spatial information of the scene.

Self-Sampling for Neural Point Cloud Consolidation

1 code implementation14 Aug 2020 Gal Metzer, Rana Hanocka, Raja Giryes, Daniel Cohen-Or

We introduce a novel technique for neural point cloud consolidation which learns from only the input point cloud.

Inductive Bias

Self-supervised Neural Architecture Search

no code implementations3 Jul 2020 Sapir Kaplan, Raja Giryes

Neural Architecture Search (NAS) has been used recently to achieve improved performance in various tasks and most prominently in image classification.

Image Classification Neural Architecture Search +1

Low Resource Sequence Tagging using Sentence Reconstruction

no code implementations ACL 2020 Tal Perl, Sriram Chaudhury, Raja Giryes

This work revisits the task of training sequence tagging models with limited resources using transfer learning.


Deep Geometric Texture Synthesis

1 code implementation30 Jun 2020 Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or

Learning and synthesizing on local geometric patches enables a genus-oblivious framework, facilitating texture transfer between shapes of different genus.

Image Generation Texture Synthesis

Face Authentication from Grayscale Coded Light Field

no code implementations31 May 2020 Dana Weitzner, David Mendlovic, Raja Giryes

Face verification is a fast-growing authentication tool for everyday systems, such as smartphones.

Face Recognition Face Verification

Point2Mesh: A Self-Prior for Deformable Meshes

2 code implementations22 May 2020 Rana Hanocka, Gal Metzer, Raja Giryes, Daniel Cohen-Or

We optimize the network weights to deform an initial mesh to shrink-wrap a single input point cloud.

On the Convergence Rate of Projected Gradient Descent for a Back-Projection based Objective

no code implementations3 May 2020 Tom Tirer, Raja Giryes

Recently, several works have considered a back-projection (BP) based fidelity term as an alternative to the common least squares (LS), and demonstrated excellent results for popular inverse problems.

A function space analysis of finite neural networks with insights from sampling theory

no code implementations15 Apr 2020 Raja Giryes

This work suggests using sampling theory to analyze the function space represented by neural networks.

PointGMM: a Neural GMM Network for Point Clouds

1 code implementation CVPR 2020 Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or

We present PointGMM, a neural network that learns to generate hGMMs which are characteristic of the shape class, and also coincide with the input point cloud.

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification

1 code implementation ECCV 2020 Moshe Lichtenstein, Prasanna Sattigeri, Rogerio Feris, Raja Giryes, Leonid Karlinsky

The field of Few-Shot Learning (FSL), or learning from very few (typically $1$ or $5$) examples per novel class (unseen during training), has received a lot of attention and significant performance advances in the recent literature.

Few-Shot Learning General Classification


no code implementations12 Mar 2020 Dor Bank, Noam Koenigstein, Raja Giryes

An autoencoder is a specific type of a neural network, which is mainly designed to encode the input into a compressed and meaningful representation, and then decode it back such that the reconstructed input is similar as possible to the original one.

BP-DIP: A Backprojection based Deep Image Prior

no code implementations11 Mar 2020 Jenny Zukerman, Tom Tirer, Raja Giryes

Deep neural networks are a very powerful tool for many computer vision tasks, including image restoration, exhibiting state-of-the-art results.

Computer Vision Deblurring +1

Introduction to deep learning

no code implementations29 Feb 2020 Lihi Shiloh-Perl, Raja Giryes

Deep Learning (DL) has made a major impact on data science in the last decade.

Motion Deblurring using Spatiotemporal Phase Aperture Coding

no code implementations18 Feb 2020 Shay Elmalem, Raja Giryes, Emanuel Marom

In this work, a computational imaging approach for motion deblurring is proposed and demonstrated.

Deblurring Image Restoration

Supervised and Unsupervised Learning of Parameterized Color Enhancement

no code implementations30 Dec 2019 Yoav Chai, Raja Giryes, Lior Wolf

We treat the problem of color enhancement as an image translation task, which we tackle using both supervised and unsupervised learning.

Image Enhancement Translation

DEGAS: Differentiable Efficient Generator Search

no code implementations2 Dec 2019 Sivan Doveh, Raja Giryes

In this work, we propose an alternative strategy for GAN search by using a method called DEGAS (Differentiable Efficient GenerAtor Search), which focuses on efficiently finding the generator in the GAN.

Image Generation Neural Architecture Search

MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification

no code implementations1 Dec 2019 Sivan Doveh, Eli Schwartz, Chao Xue, Rogerio Feris, Alex Bronstein, Raja Giryes, Leonid Karlinsky

In this work, we propose to employ tools inspired by the Differentiable Neural Architecture Search (D-NAS) literature in order to optimize the architecture for FSL without over-fitting.

Few-Shot Learning General Classification +1

Correction Filter for Single Image Super-Resolution: Robustifying Off-the-Shelf Deep Super-Resolvers

1 code implementation CVPR 2020 Shady Abu Hussein, Tom Tirer, Raja Giryes

For a known kernel, we design a closed-form correction filter that modifies the low-resolution image to match one which is obtained by another kernel (e. g. bicubic), and thus improves the results of existing pre-trained DNNs.

Image Super-Resolution Single Image Super Resolution

MonSter: Awakening the Mono in Stereo

no code implementations30 Oct 2019 Yotam Gil, Shay Elmalem, Harel Haim, Emanuel Marom, Raja Giryes

The most common methods for passive depth estimation are either a stereo or a monocular system.

Computer Vision Depth Estimation

Deep Radar Detector

no code implementations26 Jun 2019 Daniel Brodeski, Igal Bilik, Raja Giryes

While camera and LiDAR processing have been revolutionized since the introduction of deep learning, radar processing still relies on classical tools.

Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems

1 code implementation16 Jun 2019 Tom Tirer, Raja Giryes

This term encourages agreement between the projection of the optimization variable onto the row space of the linear operator and the pseudo-inverse of the linear operator ("back-projection") applied on the observations.

Deblurring Denoising +1

Image-Adaptive GAN based Reconstruction

1 code implementation12 Jun 2019 Shady Abu Hussein, Tom Tirer, Raja Giryes

In the recent years, there has been a significant improvement in the quality of samples produced by (deep) generative models such as variational auto-encoders and generative adversarial networks.

Image Super-Resolution

Baby steps towards few-shot learning with multiple semantics

no code implementations5 Jun 2019 Eli Schwartz, Leonid Karlinsky, Rogerio Feris, Raja Giryes, Alex M. Bronstein

Learning from one or few visual examples is one of the key capabilities of humans since early infancy, but is still a significant challenge for modern AI systems.

Few-Shot Image Classification

ASAP: Architecture Search, Anneal and Prune

1 code implementation8 Apr 2019 Asaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, Lihi Zelnik-Manor

In this paper, we propose a differentiable search space that allows the annealing of architecture weights, while gradually pruning inferior operations.

Neural Architecture Search

Taco-VC: A Single Speaker Tacotron based Voice Conversion with Limited Data

no code implementations6 Apr 2019 Roee Levy Leshem, Raja Giryes

Taco-VC is implemented using a single speaker Tacotron synthesizer based on Phonetic PosteriorGrams (PPGs) and a single speaker WaveNet vocoder conditioned on mel spectrograms.

Speech Enhancement Voice Conversion

Blind Visual Motif Removal from a Single Image

1 code implementation CVPR 2019 Amir Hertz, Sharon Fogel, Rana Hanocka, Raja Giryes, Daniel Cohen-Or

Many images shared over the web include overlaid objects, or visual motifs, such as text, symbols or drawings, which add a description or decoration to the image.

Lautum Regularization for Semi-supervised Transfer Learning

no code implementations2 Apr 2019 Daniel Jakubovitz, Miguel R. D. Rodrigues, Raja Giryes

We focus on the task of semi-supervised transfer learning, in which unlabeled samples from the target dataset are available during the network training on the source dataset.

Transfer Learning

LaSO: Label-Set Operations networks for multi-label few-shot learning

2 code implementations CVPR 2019 Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogerio Feris, Raja Giryes, Alex M. Bronstein

We conduct numerous experiments showing promising results for the label-set manipulation capabilities of the proposed approach, both directly (using the classification and retrieval metrics), and in the context of performing data augmentation for multi-label few-shot learning.

Data Augmentation Few-Shot Learning +1

A Greedy Approach to $\ell_{0,\infty}$ Based Convolutional Sparse Coding

no code implementations26 Dec 2018 Elad Plaut, Raja Giryes

This has the disadvantage that the reconstructed image no longer obeys the sparsity prior used in the processing.

Dictionary Learning Image Inpainting +1

TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set

no code implementations17 Dec 2018 Moran Rubin, Omer Stein, Nir A. Turko, Yoav Nygate, Darina Roitshtain, Lidor Karako, Itay Barnea, Raja Giryes, Natan T. Shaked

After this preliminary training, and after transforming the last layer of the network with new ones, we have designed an automatic classifier for the correct cell type (healthy/primary cancer/metastatic cancer) with 90-99% accuracy, although small training sets of down to several images have been used.

General Classification Image Classification +2

Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal Learning

1 code implementation30 Nov 2018 Tom Tirer, Raja Giryes

While deep neural networks exhibit state-of-the-art results in the task of image super-resolution (SR) with a fixed known acquisition process (e. g., a bicubic downscaling kernel), they experience a huge performance loss when the real observation model mismatches the one used in training.

Denoising Image Super-Resolution

Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware

no code implementations27 Nov 2018 Natan Liss, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Raja Giryes

While most works use uniform quantizers for both parameters and activations, it is not always the optimal one, and a non-uniform quantizer need to be considered.

Computer Vision Image Classification +3

An ETF view of Dropout regularization

1 code implementation14 Oct 2018 Dor Bank, Raja Giryes

Dropout is a popular regularization technique in deep learning.

MeshCNN: A Network with an Edge

1 code implementation16 Sep 2018 Rana Hanocka, Amir Hertz, Noa Fish, Raja Giryes, Shachar Fleishman, Daniel Cohen-Or

In this paper, we utilize the unique properties of the mesh for a direct analysis of 3D shapes using MeshCNN, a convolutional neural network designed specifically for triangular meshes.

3D Part Segmentation Cube Engraving Classification

Class-Aware Fully-Convolutional Gaussian and Poisson Denoising

2 code implementations20 Aug 2018 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

We propose a fully-convolutional neural-network architecture for image denoising which is simple yet powerful.

Image Denoising

Generalization Error in Deep Learning

no code implementations3 Aug 2018 Daniel Jakubovitz, Raja Giryes, Miguel R. D. Rodrigues

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing.

Computer Vision Natural Language Processing +3

RepMet: Representative-based metric learning for classification and one-shot object detection

1 code implementation12 Jun 2018 Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogerio Feris, Raja Giryes, Alex M. Bronstein

Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each category is represented by only a few examples.

Classification Few-Shot Object Detection +4

DNN or k-NN: That is the Generalize vs. Memorize Question

no code implementations17 May 2018 Gilad Cohen, Guillermo Sapiro, Raja Giryes

Moreover, the behavior of DNNs compared to the linear classifiers SVM and LR is quite the same on the training and test data regardless of whether the network generalizes.

UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks

no code implementations29 Apr 2018 Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii, Natan Liss, Raja Giryes, Alex M. Bronstein, Avi Mendelson

We present a novel method for neural network quantization that emulates a non-uniform $k$-quantile quantizer, which adapts to the distribution of the quantized parameters.


ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning

1 code implementation23 Apr 2018 Rana Hanocka, Noa Fish, Zhenhua Wang, Raja Giryes, Shachar Fleishman, Daniel Cohen-Or

The process of aligning a pair of shapes is a fundamental operation in computer graphics.

The Resistance to Label Noise in K-NN and DNN Depends on its Concentration

no code implementations30 Mar 2018 Amnon Drory, Oria Ratzon, Shai Avidan, Raja Giryes

We investigate the classification performance of K-nearest neighbors (K-NN) and deep neural networks (DNNs) in the presence of label noise.

General Classification Multi-class Classification

Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization

1 code implementation ECCV 2018 Daniel Jakubovitz, Raja Giryes

We demonstrate empirically that it leads to enhanced robustness results with a minimal change in the original network's accuracy.

DeepISP: Towards Learning an End-to-End Image Processing Pipeline

1 code implementation20 Jan 2018 Eli Schwartz, Raja Giryes, Alex M. Bronstein

We present DeepISP, a full end-to-end deep neural model of the camera image signal processing (ISP) pipeline.

Demosaicking Denoising

Mathematics of Deep Learning

no code implementations13 Dec 2017 Rene Vidal, Joan Bruna, Raja Giryes, Stefano Soatto

Recently there has been a dramatic increase in the performance of recognition systems due to the introduction of deep architectures for representation learning and classification.

General Classification Representation Learning

Learned Convolutional Sparse Coding

2 code implementations1 Nov 2017 Hillel Sreter, Raja Giryes

We propose a convolutional recurrent sparse auto-encoder model.

Image Denoising Image Inpainting

Image Restoration by Iterative Denoising and Backward Projections

1 code implementation18 Oct 2017 Tom Tirer, Raja Giryes

In this work, we propose an alternative method for solving inverse problems using off-the-shelf denoisers, which requires less parameter tuning.

Deblurring Denoising +3

Deep Class Aware Denoising

1 code implementation6 Jan 2017 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

We further show that a significant boost in performance of up to $0. 4$ dB PSNR can be achieved by making our network class-aware, namely, by fine-tuning it for images belonging to a specific semantic class.

Image Denoising Image Enhancement

Deep Convolutional Denoising of Low-Light Images

2 code implementations6 Jan 2017 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

Poisson distribution is used for modeling noise in photon-limited imaging.


Generalization Error of Invariant Classifiers

no code implementations14 Oct 2016 Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues

We show that whereas the generalization error of a non-invariant classifier is proportional to the complexity of the input space, the generalization error of an invariant classifier is proportional to the complexity of the base space.

Robust Large Margin Deep Neural Networks

no code implementations26 May 2016 Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues

The generalization error of deep neural networks via their classification margin is studied in this work.

Poisson Inverse Problems by the Plug-and-Play scheme

no code implementations8 Nov 2015 Arie Rond, Raja Giryes, Michael Elad

In this work we suggest a novel method for coupling Gaussian denoising algorithms to Poisson noisy inverse problems, which is based on a general approach termed "Plug-and-Play".


Postprocessing of Compressed Images via Sequential Denoising

no code implementations30 Oct 2015 Yehuda Dar, Alfred M. Bruckstein, Michael Elad, Raja Giryes

In this work we propose a novel postprocessing technique for compression-artifact reduction.

Image Denoising

Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?

no code implementations30 Apr 2015 Raja Giryes, Guillermo Sapiro, Alex M. Bronstein

Three important properties of a classification machinery are: (i) the system preserves the core information of the input data; (ii) the training examples convey information about unseen data; and (iii) the system is able to treat differently points from different classes.

Dictionary Learning General Classification +1

On the Stability of Deep Networks

no code implementations18 Dec 2014 Raja Giryes, Guillermo Sapiro, Alex M. Bronstein

In particular, we formally prove in the longer version that DNN with random Gaussian weights perform a distance-preserving embedding of the data, with a special treatment for in-class and out-of-class data.

Sparsity Based Methods for Overparameterized Variational Problems

no code implementations20 May 2014 Raja Giryes, Michael Elad, Alfred M. Bruckstein

Two complementary approaches have been extensively used in signal and image processing leading to novel results, the sparse representation methodology and the variational strategy.

Denoising Optical Flow Estimation

Sparsity Based Poisson Denoising with Dictionary Learning

no code implementations17 Sep 2013 Raja Giryes, Michael Elad

In cases of high SNR, several transformations exist so as to convert the Poisson noise into an additive i. i. d.

Denoising Dictionary Learning

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