The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XL-1/W5
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
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

  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 N. Tatar et al.
  • 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.