Detecting buildings in aerial images
Computer Vision, Graphics, and Image Processing
Detecting clouds and cloud shadows on aerial photographs
Pattern Recognition Letters
Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Shadow segmentation and classification in a constrained environment
CVGIP: Image Understanding
Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Combining color and geometry for the active, visual recognition of shadows
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
A shadow detection method for remote sensing images using affinity propagation algorithm
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Data mining applications in hydrocarbon exploration
Artificial Intelligence Review
Lunar terrain and albedo reconstruction of the apollo 15 zone
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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Image shadow segmentation has become a major issue in satellite remote sensing because of the recent commercial availability of high-resolution images. Detecting shadows is important for successfully carrying out applications such as change detection, land monitoring, object recognition, scene reconstruction, colour correction, etc. This paper presents a simple and effective procedure to segment shadow regions on high-resolution colour satellite images. The method applies a region growing process on a specific band (namely, the c 3 component of the c 1 c 2 c 3 colour space). To gain in robustness and precision, the region expansion also imposes a restriction on the saturation and intensity values of the shadow pixels, as well as on their edge gradients. The proposed method has been successfully tested on QuickBird images acquired under different lighting conditions and covering both urban and rural areas.