Detail publikace
Image demosaicing using Deep Image Prior
BALUŠÍK, P.
Originální název
Image demosaicing using Deep Image Prior
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
The paper focuses on the problem of image demosaicing using the deep image prior. The deep image prior (DIP) is an uncommon concept that uses a generative neural network which, however, utilizes only the degraded image as the input for training. A novel method for image demosaicing is proposed, based on DIP, and it is compared with common demosaicing methods. In terms of the objective PSNR and SSIM values, the proposed method proved to be comparable with a widely used Malvar’s demosaicing method. Nevertheless, subjectively, DIP produces demosaiced images comparable with the superior Menon’s algorithm. Unfortunately, the proposed method turned out to be computationally immensely challenging.
Klíčová slova
demosaicing, debayerization, color filter array, deep image prior
Autoři
BALUŠÍK, P.
Vydáno
25. 4. 2023
Nakladatel
Brno University of Technology, Faculty of Electrical Engineering and Communication
Místo
Brno
ISBN
978-80-214-6154-3
Kniha
Proceedings II of the 29th Conference STUDENT EEICT 2023 Selected papers
Edice
1
ISSN
2788-1334
Periodikum
Proceedings II of the Conference STUDENT EEICT
Stát
Česká republika
Strany od
17
Strany do
20
Strany počet
4
URL
BibTex
@inproceedings{BUT184280,
author="Peter {Balušík}",
title="Image demosaicing using Deep Image Prior",
booktitle="Proceedings II of the 29th Conference STUDENT EEICT 2023 Selected papers",
year="2023",
series="1",
journal="Proceedings II of the Conference STUDENT EEICT",
pages="17--20",
publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
address="Brno",
doi="10.13164/eeict.2023.17",
isbn="978-80-214-6154-3",
issn="2788-1334",
url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf"
}