Publication detail
Image demosaicing using Deep Image Prior
BALUŠÍK, P.
Original Title
Image demosaicing using Deep Image Prior
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
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.
Keywords
demosaicing, debayerization, color filter array, deep image prior
Authors
BALUŠÍK, P.
Released
25. 4. 2023
Publisher
Brno University of Technology, Faculty of Electrical Engineering and Communication
Location
Brno
ISBN
978-80-214-6154-3
Book
Proceedings II of the 29th Conference STUDENT EEICT 2023 Selected papers
Edition
1
ISBN
2788-1334
Periodical
Proceedings II of the Conference STUDENT EEICT
State
Czech Republic
Pages from
17
Pages to
20
Pages count
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"
}