Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 713-717, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-713-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
A NEW OBJECT-BASED FRAMEWORK TO DETECT SHODOWS IN HIGH-RESOLUTION SATELLITE IMAGERY OVER URBAN AREAS
N. Tatar, M. Saadatseresht, H. Arefi, and A. Hadavand School of Surveying and Geospatial Information Engineering, College of Engineering, University of Tehran, Tehran, Iran
Keywords: Shadow Detection, Spectral Index, High resolution satellite imagery, Segmentation, Object-based, Majority Voting Abstract. In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.
Conference paper (PDF, 1204 KB)


Citation: Tatar, N., Saadatseresht, M., Arefi, H., and Hadavand, A.: A NEW OBJECT-BASED FRAMEWORK TO DETECT SHODOWS IN HIGH-RESOLUTION SATELLITE IMAGERY OVER URBAN AREAS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 713-717, https://doi.org/10.5194/isprsarchives-XL-1-W5-713-2015, 2015.

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