EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES
A method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-09-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/803/2017/isprs-archives-XLII-2-W7-803-2017.pdf |
| _version_ | 1819106685649682432 |
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| author | X. G. Lin X. G. Ning |
| author_facet | X. G. Lin X. G. Ning |
| author_sort | X. G. Lin |
| collection | DOAJ |
| description | A method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determined by cross verification of the detected corners and line segments, and these two types of features are rasterized. Second, a human settlement index image is built based on the density and distance of the right-angle-corners and right-angle-sides in a local region. Finally, the polygons of human settlements are generated through binary thresholding of the index image, conversion from raster format to vector format, and sieving. Three images are used for testing the proposed method. The experimental results suggest that our proposed method has higher accuracy than the existed method. Specifically, the correctness, completeness, and quality of our method are 6.76 %, 10.12 %, 12.14 % respectively higher than the existed method. |
| first_indexed | 2024-12-22T02:42:04Z |
| format | Article |
| id | doaj.art-400efbc512a94935bbcd7898632f8561 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-22T02:42:04Z |
| publishDate | 2017-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-400efbc512a94935bbcd7898632f85612022-12-21T18:41:36ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-2-W780380710.5194/isprs-archives-XLII-2-W7-803-2017EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDESX. G. Lin0X. G. Ning1Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, No. 28, Lianhuachixi Road, Haidian District, Beijing 100830, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, No. 28, Lianhuachixi Road, Haidian District, Beijing 100830, ChinaA method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determined by cross verification of the detected corners and line segments, and these two types of features are rasterized. Second, a human settlement index image is built based on the density and distance of the right-angle-corners and right-angle-sides in a local region. Finally, the polygons of human settlements are generated through binary thresholding of the index image, conversion from raster format to vector format, and sieving. Three images are used for testing the proposed method. The experimental results suggest that our proposed method has higher accuracy than the existed method. Specifically, the correctness, completeness, and quality of our method are 6.76 %, 10.12 %, 12.14 % respectively higher than the existed method.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/803/2017/isprs-archives-XLII-2-W7-803-2017.pdf |
| spellingShingle | X. G. Lin X. G. Ning EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES |
| title_full | EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES |
| title_fullStr | EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES |
| title_full_unstemmed | EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES |
| title_short | EXTRACTION OF HUMAN SETTLEMENTS FROM HIGH RESOLUTION REMOTE SENSING IMAGERY BY FUSING BOTH RIGHT-ANGLE CORNERS AND RIGHT-ANGLE SIDES |
| title_sort | extraction of human settlements from high resolution remote sensing imagery by fusing both right angle corners and right angle sides |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/803/2017/isprs-archives-XLII-2-W7-803-2017.pdf |
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