GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector
As the significance of meticulous and precise map creation grows in modern Geographic Information Systems (GISs), urban planning, disaster response, and other domains, the necessity for sophisticated map generation technology has become increasingly evident. In response to this demand, this paper pu...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/23/10963 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846124480774012928 |
|---|---|
| author | Jongwook Si Sungyoung Kim |
| author_facet | Jongwook Si Sungyoung Kim |
| author_sort | Jongwook Si |
| collection | DOAJ |
| description | As the significance of meticulous and precise map creation grows in modern Geographic Information Systems (GISs), urban planning, disaster response, and other domains, the necessity for sophisticated map generation technology has become increasingly evident. In response to this demand, this paper puts forward a technique based on Generative Adversarial Networks (GANs) for converting aerial imagery into high-quality maps. The proposed method, comprising a generator and a discriminator, introduces novel strategies to overcome existing challenges; namely, the use of a Canny edge detector and Residual Blocks. The proposed loss function enhances the generator’s performance by assigning greater weight to edge regions using the Canny edge map and eliminating superfluous information. This approach enhances the visual quality of the generated maps and ensures the accurate capture of fine details. The experimental results demonstrate that this method generates maps of superior visual quality, achieving outstanding performance compared to existing methodologies. The results show that the proposed technology has significant potential for practical applications in a range of real-world scenarios. |
| format | Article |
| id | doaj-art-02fef30001544ca9a62b5324e7a71ff1 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-02fef30001544ca9a62b5324e7a71ff12024-12-13T16:22:19ZengMDPI AGApplied Sciences2076-34172024-11-0114231096310.3390/app142310963GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge DetectorJongwook Si0Sungyoung Kim1Department of Computer AI Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Republic of KoreaDepartment of Computer Engineering, Kumoh National Institute of Technology, Gumi 39177, Republic of KoreaAs the significance of meticulous and precise map creation grows in modern Geographic Information Systems (GISs), urban planning, disaster response, and other domains, the necessity for sophisticated map generation technology has become increasingly evident. In response to this demand, this paper puts forward a technique based on Generative Adversarial Networks (GANs) for converting aerial imagery into high-quality maps. The proposed method, comprising a generator and a discriminator, introduces novel strategies to overcome existing challenges; namely, the use of a Canny edge detector and Residual Blocks. The proposed loss function enhances the generator’s performance by assigning greater weight to edge regions using the Canny edge map and eliminating superfluous information. This approach enhances the visual quality of the generated maps and ensures the accurate capture of fine details. The experimental results demonstrate that this method generates maps of superior visual quality, achieving outstanding performance compared to existing methodologies. The results show that the proposed technology has significant potential for practical applications in a range of real-world scenarios.https://www.mdpi.com/2076-3417/14/23/10963GANaerial imagemap generationedge detectionimage-to-image translation |
| spellingShingle | Jongwook Si Sungyoung Kim GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector Applied Sciences GAN aerial image map generation edge detection image-to-image translation |
| title | GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector |
| title_full | GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector |
| title_fullStr | GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector |
| title_full_unstemmed | GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector |
| title_short | GAN-Based Map Generation Technique of Aerial Image Using Residual Blocks and Canny Edge Detector |
| title_sort | gan based map generation technique of aerial image using residual blocks and canny edge detector |
| topic | GAN aerial image map generation edge detection image-to-image translation |
| url | https://www.mdpi.com/2076-3417/14/23/10963 |
| work_keys_str_mv | AT jongwooksi ganbasedmapgenerationtechniqueofaerialimageusingresidualblocksandcannyedgedetector AT sungyoungkim ganbasedmapgenerationtechniqueofaerialimageusingresidualblocksandcannyedgedetector |