The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-1/W5
https://doi.org/10.5194/isprsarchives-XL-1-W5-713-2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-713-2015
11 Dec 2015
 | 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

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.