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Volume: 2 | Article ID: art00020
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Automatic Noise Analysis on Still Life Chart
  DOI :  10.2352/issn.2694-118X.2021.LIM-101  Published OnlineSeptember 2021
Abstract

In this paper, we tackle the issue of estimating the noise level of a camera, on its processed still images and as perceived by the user. Commonly, the characterization of the noise level of a camera is done using objective metrics determined on charts containing uniform patches at a given condition. These methods can lead to inadequate characterizations of the noise of a camera because cameras often incorporate denoising algorithms that are more efficient on uniform areas than on areas containing details. Therefore, in this paper, we propose a method to estimate the perceived noise level on natural areas of a still-life chart. Our method is based on a deep convolutional network trained with ground truth quality scores provided by expert annotators. Our experimental evaluation shows that our approach strongly matches human evaluations.

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  Cite this article 

Salim Belkarfa, Ahmed Hakim Choukarah, Marcelin Tworski, "Automatic Noise Analysis on Still Life Chartin Proc. IS&T London Imaging Meeting 2021: Imaging for Deep Learning,  2021,  pp 101 - 105,  https://doi.org/10.2352/issn.2694-118X.2021.LIM-101

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