About

Salt-and-pepper noise is a form of noise sometimes seen on images. It is also known as impulse noise. This noise can be caused by sharp and sudden disturbances in the image signal. It presents itself as sparsely occurring white and black pixels.

( Image credit: NAMF )

Benchmarks

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Datasets

Greatest papers with code

Noise2Noise: Learning Image Restoration without Clean Data

ICML 2018 NVlabs/noise2noise

We apply basic statistical reasoning to signal reconstruction by machine learning -- learning to map corrupted observations to clean signals -- with a simple and powerful conclusion: it is possible to learn to restore images by only looking at corrupted examples, at performance at and sometimes exceeding training using clean data, without explicit image priors or likelihood models of the corruption.

IMAGE RESTORATION SALT-AND-PEPPER NOISE REMOVAL

Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations

18 Aug 2019llmpass/medianDenoise

We propose a deep fully convolutional neural network with a new type of layer, named median layer, to restore images contaminated by the salt-and-pepper (s&p) noise.

SALT-AND-PEPPER NOISE REMOVAL

NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal

17 Oct 2019ProfHubert/NAMF

In this paper, a novel algorithm called a non-local adaptive mean filter (NAMF) for removing salt-and-pepper (SAP) noise from corrupted images is presented.

SALT-AND-PEPPER NOISE REMOVAL