Heritage applications of landscape design in environmental art based on image style migration
To create environmental art on the basis of preserving environmental and ecological resources, landscape design considers the peaceful coexistence of art and ecology. In picture generation and rendering for landscape design, image style migration techniques are frequently employed, however their qua...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123023006126 |
| _version_ | 1797385165388906496 |
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| author | Xuyang Guo Jun Ma |
| author_facet | Xuyang Guo Jun Ma |
| author_sort | Xuyang Guo |
| collection | DOAJ |
| description | To create environmental art on the basis of preserving environmental and ecological resources, landscape design considers the peaceful coexistence of art and ecology. In picture generation and rendering for landscape design, image style migration techniques are frequently employed, however their quality is still lacking at this point. In order to enhance the migration effect, the study builds an image style migration model for landscape design, tries to employ a multi-scale discriminator, and introduces a content feature mapping module and a migration learning approach. According to the test results, adding the content feature mapping module enhanced the feature mapping effect of the photographs. The revised model's peak signal-to-noise ratio and similarity assessment indexes were 17.42 and 0.91, respectively, and the model's generated images were less distorted. While the Frey interval distance was only 16.32 and the generated images were strongly correlated, the model had good generalisation. The addition of migration learning somewhat improves all of the measures. In conclusion, the research findings are beneficial for the expression of environmental art in landscape design, and the model's picture creation assessment index and stability are both good. |
| first_indexed | 2024-03-08T21:50:11Z |
| format | Article |
| id | doaj.art-a04a5910481740998096d6a6bd3ee683 |
| institution | Directory Open Access Journal |
| issn | 2590-1230 |
| language | English |
| last_indexed | 2024-03-08T21:50:11Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj.art-a04a5910481740998096d6a6bd3ee6832023-12-20T07:35:54ZengElsevierResults in Engineering2590-12302023-12-0120101485Heritage applications of landscape design in environmental art based on image style migrationXuyang Guo0Jun Ma1School of Architectural Art and Design, LuXun Academy of Fine Arts, Shenyang, 110004, ChinaSchool of Visual Communication Design, LuXun Academy of Fine Arts, Dalian, 116000, China; Corresponding author.To create environmental art on the basis of preserving environmental and ecological resources, landscape design considers the peaceful coexistence of art and ecology. In picture generation and rendering for landscape design, image style migration techniques are frequently employed, however their quality is still lacking at this point. In order to enhance the migration effect, the study builds an image style migration model for landscape design, tries to employ a multi-scale discriminator, and introduces a content feature mapping module and a migration learning approach. According to the test results, adding the content feature mapping module enhanced the feature mapping effect of the photographs. The revised model's peak signal-to-noise ratio and similarity assessment indexes were 17.42 and 0.91, respectively, and the model's generated images were less distorted. While the Frey interval distance was only 16.32 and the generated images were strongly correlated, the model had good generalisation. The addition of migration learning somewhat improves all of the measures. In conclusion, the research findings are beneficial for the expression of environmental art in landscape design, and the model's picture creation assessment index and stability are both good.http://www.sciencedirect.com/science/article/pii/S2590123023006126Image style migrationLandscape designEnvironmental artGenerative adversarial networksTransfer learning |
| spellingShingle | Xuyang Guo Jun Ma Heritage applications of landscape design in environmental art based on image style migration Results in Engineering Image style migration Landscape design Environmental art Generative adversarial networks Transfer learning |
| title | Heritage applications of landscape design in environmental art based on image style migration |
| title_full | Heritage applications of landscape design in environmental art based on image style migration |
| title_fullStr | Heritage applications of landscape design in environmental art based on image style migration |
| title_full_unstemmed | Heritage applications of landscape design in environmental art based on image style migration |
| title_short | Heritage applications of landscape design in environmental art based on image style migration |
| title_sort | heritage applications of landscape design in environmental art based on image style migration |
| topic | Image style migration Landscape design Environmental art Generative adversarial networks Transfer learning |
| url | http://www.sciencedirect.com/science/article/pii/S2590123023006126 |
| work_keys_str_mv | AT xuyangguo heritageapplicationsoflandscapedesigninenvironmentalartbasedonimagestylemigration AT junma heritageapplicationsoflandscapedesigninenvironmentalartbasedonimagestylemigration |