A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments
Shadow in remote sensing images can obscure important details of land features, making shadow detection crucial for enhancing the accuracy of subsequent analyses and applications. Current shadow detection methods primarily rely on the spectral information of images, which can often result in shadow...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/9/4899 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849322478790246400 |
|---|---|
| author | Huagui Xu Jingxing Zhu Feng Wang Hongjian You Wenzhi Wang |
| author_facet | Huagui Xu Jingxing Zhu Feng Wang Hongjian You Wenzhi Wang |
| author_sort | Huagui Xu |
| collection | DOAJ |
| description | Shadow in remote sensing images can obscure important details of land features, making shadow detection crucial for enhancing the accuracy of subsequent analyses and applications. Current shadow detection methods primarily rely on the spectral information of images, which can often result in shadow misdetection due to the phenomenon of spectral confusion of different objects. To mitigate this issue, we propose a method that combines topography and spectra (CTS). Firstly, we introduce a new DEM-based shadow coarse detection method to obtain the DEM rough shadow mask, which uses a relationship between the magnitude of terrain height angle and solar elevation angle to determine shadow properties. Then, we use the MC3 (modified C3 component) index-based shadow fine detection method to obtain an MC3 mean map, which includes image enhancement with a stretching process and multi-scale superpixel segmentation. We then derive the Shadow pixel Proportion Map (SPM) by counting the DEM rough shadow mask in terms of superpixels. The Joint Shadow probability Map (JSM) is obtained by combining the SPM and the MC3 mean map with specific weights. Finally, a multi-level Otsu threshold method is applied to the JSM to generate the shadow mask. We compare the proposed CTS method against several state-of-the-art algorithms through both qualitative assessments and quantitative metrics. The results show that the CTS method demonstrates superior accuracy and consistency in detecting true shadows, achieving an average overall accuracy of 95.81% on mountainous remote sensing images. |
| format | Article |
| id | doaj-art-900ebe2ecbc44f8fa6e9a47b638ad8a4 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-900ebe2ecbc44f8fa6e9a47b638ad8a42025-08-20T03:49:22ZengMDPI AGApplied Sciences2076-34172025-04-01159489910.3390/app15094899A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous EnvironmentsHuagui Xu0Jingxing Zhu1Feng Wang2Hongjian You3Wenzhi Wang4Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory of Technology in Geo-Spatial Information Processing and Application System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory of Technology in Geo-Spatial Information Processing and Application System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory of Technology in Geo-Spatial Information Processing and Application System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory of Technology in Geo-Spatial Information Processing and Application System, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaShadow in remote sensing images can obscure important details of land features, making shadow detection crucial for enhancing the accuracy of subsequent analyses and applications. Current shadow detection methods primarily rely on the spectral information of images, which can often result in shadow misdetection due to the phenomenon of spectral confusion of different objects. To mitigate this issue, we propose a method that combines topography and spectra (CTS). Firstly, we introduce a new DEM-based shadow coarse detection method to obtain the DEM rough shadow mask, which uses a relationship between the magnitude of terrain height angle and solar elevation angle to determine shadow properties. Then, we use the MC3 (modified C3 component) index-based shadow fine detection method to obtain an MC3 mean map, which includes image enhancement with a stretching process and multi-scale superpixel segmentation. We then derive the Shadow pixel Proportion Map (SPM) by counting the DEM rough shadow mask in terms of superpixels. The Joint Shadow probability Map (JSM) is obtained by combining the SPM and the MC3 mean map with specific weights. Finally, a multi-level Otsu threshold method is applied to the JSM to generate the shadow mask. We compare the proposed CTS method against several state-of-the-art algorithms through both qualitative assessments and quantitative metrics. The results show that the CTS method demonstrates superior accuracy and consistency in detecting true shadows, achieving an average overall accuracy of 95.81% on mountainous remote sensing images.https://www.mdpi.com/2076-3417/15/9/4899remote sensing imagesshadow detectionmethod that combines topography and spectra (CTS)DEMmulti-scale superpixel segmentation |
| spellingShingle | Huagui Xu Jingxing Zhu Feng Wang Hongjian You Wenzhi Wang A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments Applied Sciences remote sensing images shadow detection method that combines topography and spectra (CTS) DEM multi-scale superpixel segmentation |
| title | A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments |
| title_full | A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments |
| title_fullStr | A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments |
| title_full_unstemmed | A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments |
| title_short | A Shadow Detection Method Combining Topography and Spectra for Remote Sensing Images in Mountainous Environments |
| title_sort | shadow detection method combining topography and spectra for remote sensing images in mountainous environments |
| topic | remote sensing images shadow detection method that combines topography and spectra (CTS) DEM multi-scale superpixel segmentation |
| url | https://www.mdpi.com/2076-3417/15/9/4899 |
| work_keys_str_mv | AT huaguixu ashadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT jingxingzhu ashadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT fengwang ashadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT hongjianyou ashadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT wenzhiwang ashadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT huaguixu shadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT jingxingzhu shadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT fengwang shadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT hongjianyou shadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments AT wenzhiwang shadowdetectionmethodcombiningtopographyandspectraforremotesensingimagesinmountainousenvironments |