AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION
Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-05-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/393/2017/isprs-archives-XLII-1-W1-393-2017.pdf |
| _version_ | 1818286422625353728 |
|---|---|
| author | J. Tian T. Krauß P. d’Angelo |
| author_facet | J. Tian T. Krauß P. d’Angelo |
| author_sort | J. Tian |
| collection | DOAJ |
| description | Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich. |
| first_indexed | 2024-12-13T01:24:21Z |
| format | Article |
| id | doaj.art-34c3f8aa13034e5d95b8a8cbe4a29419 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-13T01:24:21Z |
| publishDate | 2017-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-34c3f8aa13034e5d95b8a8cbe4a294192022-12-22T00:04:09ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-05-01XLII-1-W139339710.5194/isprs-archives-XLII-1-W1-393-2017AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTIONJ. Tian0T. Krauß1P. d’Angelo2German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, GermanyGerman Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, GermanyGerman Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, GermanyAutomatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/393/2017/isprs-archives-XLII-1-W1-393-2017.pdf |
| spellingShingle | J. Tian T. Krauß P. d’Angelo AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION |
| title_full | AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION |
| title_fullStr | AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION |
| title_full_unstemmed | AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION |
| title_short | AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION |
| title_sort | automatic rooftop extraction in stereo imagery using distance and building shape regularized level set evolution |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/393/2017/isprs-archives-XLII-1-W1-393-2017.pdf |
| work_keys_str_mv | AT jtian automaticrooftopextractioninstereoimageryusingdistanceandbuildingshaperegularizedlevelsetevolution AT tkrauß automaticrooftopextractioninstereoimageryusingdistanceandbuildingshaperegularizedlevelsetevolution AT pdangelo automaticrooftopextractioninstereoimageryusingdistanceandbuildingshaperegularizedlevelsetevolution |