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Denoising

308 papers with code ยท Computer Vision

Denoising is the task of removing noise from an image.

( Image credit: Beyond a Gaussian Denoiser )

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Latest papers without code

Pattern Denoising in Molecular Associative Memory using Pairwise Markov Random Field Models

28 May 2020

We propose an in silico molecular associative memory model for pattern learning, storage and denoising using Pairwise Markov Random Field (PMRF) model.

DENOISING

Survey: Machine Learning in Production Rendering

26 May 2020

In the past few years, machine learning-based approaches have had some great success for rendering animated feature films.

DENOISING

Bayesian Conditional GAN for MRI Brain Image Synthesis

25 May 2020

Compared with the conventional Bayesian neural network with Monte Carlo dropout, results of the proposed method reach a significant lower RMSE with a p-value of 0. 0186.

CALIBRATION DENOISING IMAGE GENERATION SUPER-RESOLUTION

Lite Audio-Visual Speech Enhancement

24 May 2020

Previous studies have confirmed the effectiveness of incorporating visual information into speech enhancement (SE) systems.

DENOISING SPEECH ENHANCEMENT

Revisiting Role of Autoencoders in Adversarial Settings

21 May 2020

Through the comprehensive experimental results and analysis, this paper presents the inherent property of adversarial robustness in the autoencoders.

ADVERSARIAL DEFENSE DENOISING

An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges

21 May 2020

All of this helps conclude that, thanks to alterations in their structure as well as their objective function, autoencoders may be the core of a possible solution to many problems which can be modeled as a transformation of the feature space.

IMAGE DENOISING REPRESENTATION LEARNING

Attention-based network for low-light image enhancement

20 May 2020

Extensive experiments demonstrate the superiority of the proposed network in terms of suppressing the chromatic aberration and noise artifacts in enhancement, especially when the low-light image has severe noise.

DENOISING LOW-LIGHT IMAGE ENHANCEMENT

One Size Fits All: Can We Train One Denoiser for All Noise Levels?

19 May 2020

The de facto training protocol to achieve this goal is to train the estimator with noisy samples whose noise levels are uniformly distributed across the range of interest.

IMAGE DENOISING

Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks

19 May 2020

It is necessary to reduce the dose of CTP for routine applications due to the high radiation exposure from the repeated scans, where image denoising is necessary to achieve a reliable diagnosis.

IMAGE DENOISING

Inverse problems with second-order Total Generalized Variation constraints

19 May 2020

Total Generalized Variation (TGV) has recently been introduced as penalty functional for modelling images with edges as well as smooth variations.

IMAGE DENOISING