The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-3/W10
07 Feb 2020
 | 07 Feb 2020


W. X. Zhang, G. Q. Zhou, T. Yue, B. Jia, X. Bao, Y. S. Huang, and Q. Y. Wang

Keywords: Orthophoto, Artificial Shadow, Shadow Detection, Global Relaxation Matching, Neighbourhood Spatial Structure, Similarity Evaluation

Abstract. Shadows are ubiquitous in high-resolution images, especially in urban regions where there are more serious shadow occlusions. In order to improve the detection effect of shadows, this paper analyzes the characteristics and properties of shadows in orthophotos, and proposes an orthophoto shadow detection method under artificial shadow. Firstly, the shadow modeling tool is used to calculate the shadow regions (i.e. artificial shadow) caused by the building obstructing the sun's rays. Secondly, the relaxation matching algorithm is extended by the position and the shape of the shadow polygon as characteristic constraints. The relaxation matching algorithm is extended by the position and shape as shadow polygon’s characteristic constraints. Thirdly, the feature constraint value is calculated which between the shadow polygons of the two images. The correlation coefficient is used to obtain the initial probability value of each shadow polygon in the orthophoto. Finally, the optimal solution is obtained by continuous correction and iteration of the initial probability value. The method performs an overall matching of the two images and obtains the position of the shadow regions of the buildings in the orthophoto image. Experiment shows that this method reduces the mismatch rate and improves the matching accuracy. This method can detect shadow regions of buildings in orthophoto quickly and efficiently.