A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design

With the rapid development of networks and the emergence of various devices, images have become the main form of information transmission in real life. Image restoration, as an important branch of image processing, can be applied to real-life situations such as pixel loss in image transmission or ne...

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Autor principal:	Chen Li
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/9a962eb4105d4f0c91daf254f80f23e4
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id	oai:doaj.org-article:9a962eb4105d4f0c91daf254f80f23e4
record_format	dspace
spelling	oai:doaj.org-article:9a962eb4105d4f0c91daf254f80f23e42021-11-08T02:35:48ZA Partial Differential Equation-Based Image Restoration Method in Environmental Art Design1687-913910.1155/2021/4040497https://doaj.org/article/9a962eb4105d4f0c91daf254f80f23e42021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4040497https://doaj.org/toc/1687-9139With the rapid development of networks and the emergence of various devices, images have become the main form of information transmission in real life. Image restoration, as an important branch of image processing, can be applied to real-life situations such as pixel loss in image transmission or network prone to packet loss. However, existing image restoration algorithms have disadvantages such as fuzzy restoration effect and slow speed; to solve such problems, this paper adopts a dual discriminator model based on generative adversarial networks, which effectively improves the restoration accuracy by adding local discriminators to track the information of local missing regions of images. However, the model is not optimistic in generating reasonable semantic information, and for this reason, a partial differential equation-based image restoration model is proposed. A classifier and a feature extraction network are added to the dual discriminator model to provide category, style, and content loss constraints to the generative network, respectively. To address the training instability problem of discriminator design, spectral normalization is introduced to the discriminator design. Extensive experiments are conducted on a data dataset of partial differential equations, and the results show that the partial differential equation-based image restoration model provides significant improvements in image restoration over previous methods and that image restoration techniques are exceptionally important in the application of environmental art design.Chen LiHindawi LimitedarticlePhysicsQC1-999ENAdvances in Mathematical Physics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Chen Li A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
description	With the rapid development of networks and the emergence of various devices, images have become the main form of information transmission in real life. Image restoration, as an important branch of image processing, can be applied to real-life situations such as pixel loss in image transmission or network prone to packet loss. However, existing image restoration algorithms have disadvantages such as fuzzy restoration effect and slow speed; to solve such problems, this paper adopts a dual discriminator model based on generative adversarial networks, which effectively improves the restoration accuracy by adding local discriminators to track the information of local missing regions of images. However, the model is not optimistic in generating reasonable semantic information, and for this reason, a partial differential equation-based image restoration model is proposed. A classifier and a feature extraction network are added to the dual discriminator model to provide category, style, and content loss constraints to the generative network, respectively. To address the training instability problem of discriminator design, spectral normalization is introduced to the discriminator design. Extensive experiments are conducted on a data dataset of partial differential equations, and the results show that the partial differential equation-based image restoration model provides significant improvements in image restoration over previous methods and that image restoration techniques are exceptionally important in the application of environmental art design.
format	article
author	Chen Li
author_facet	Chen Li
author_sort	Chen Li
title	A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
title_short	A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
title_full	A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
title_fullStr	A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
title_full_unstemmed	A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design
title_sort	partial differential equation-based image restoration method in environmental art design
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/9a962eb4105d4f0c91daf254f80f23e4
work_keys_str_mv	AT chenli apartialdifferentialequationbasedimagerestorationmethodinenvironmentalartdesign AT chenli partialdifferentialequationbasedimagerestorationmethodinenvironmentalartdesign
_version_	1718443212893323264

A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design

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