Algorithms for multi-frame image super-resolution under applicative noise based on deep neural networks

Algorithms for multi-frame image super-resolution under applicative noise based on deep neural networks

The article describes algorithms for multi-frame image super-resolution, which recover high-resolution images from a sequence of low-resolution images of the same scene under applicative noise. Applicative noise generates local regions of outlying observations in each image and reduces the image res...

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Bibliographic Details
Main Authors: S.V. Savvin, A.A. Sirota
Format: Article
Language:English
Published: Samara National Research University 2022-02-01
Series:Компьютерная оптика
Subjects:
digital image processing
multi-frame superresolution
convolutional neural networks
deep learning
applicative noise
Online Access:https://computeroptics.ru/eng/KO/Annot/KO46-1/460116e.html

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