Abstract
Although many efforts have been made on building shadow detection from aerial images, little research on simultaneous shadows detection on both building roofs and grounds has been presented. Hence, this paper proposes a new method for simultaneous shadow detection on ghost image. In the proposed method, a corner point on shadow boundary is selected and its 3D approximate coordinate is calculated through photogrammetric collinear equation on the basis of assumption of average elevation within the aerial image. The 3D coordinates of the shadow corner point on shadow boundary is used to calculate the solar zenith angle and the solar altitude angle. The shadow areas on the ground, at the moment of aerial photograph shooting are determined by the solar zenith angle and the solar altitude angle with the prior information of the digital building model (DBM). Using the relationship between the shadows of each building and the height difference of buildings, whether there exists a shadow on the building roof is determined, and the shadow area on the building roof on the ghost image is detected on the basis of the DBM. High-resolution aerial images located in the City of Denver, Colorado, USA are used to verify the proposed method. The experimental results demonstrate that the shadows of the 120 buildings in the study area are completely detected, and the success rate is 15% higher than the traditional shadow detection method based on shadow features. Especially, when the shadows occur on the ground and on the buildings roofs, the successful rate of shadow detection can be improved by 9.42% and 33.33% respectively.
Highlights
The high resolution urban aerial images are widely used in the applications of digital city building
To detect the shadows of the buildings in high-resolution urban imagery, this paper proposes a method that uses the digital building model (DBM) as an over-model to detect the shadows on both building roofs and grounds simultaneously
The solar zenith angle and the solar altitude angle are determined by selecting the geographical information of the corner point on the shadow boundary in the aerial image
Summary
The high resolution urban aerial images are widely used in the applications of digital city building. Liu et al [8] proposed an object-oriented classification method which is based on the relationship between the shadow and the adjacent non-shadow areas They found that the method can effectively detect the shadow areas in the image. Because the prior information, such as scenes, light source, etc., are not required, these types of methods are widely used for shadow detection These methods still have several deficiencies, such as (1) the color features have a poor resolving power; (2) the pixel values of the texture features are need to be computed around the detection area; (3) the optimal threshold is difficult to be determined or selected, since some of the parameters are variable in different scenic areas; (4) the edge detection method is based on the edge of features, but the true shadow edges are difficult to be distinguished from other edges. The efficiency of the above methods is greatly impacted with various practical scenes
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