Research Papers

Shadow detection for color remotely sensed images based on multi-feature integration

[+] Author Affiliations
Jiahang Liu

Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai 200240, China

Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, China

Deren Li

Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan 430079, China

Tao Fang

Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai 200240, China

J. Appl. Remote Sens. 6(1), 063521 (Apr 23, 2012). doi:10.1117/1.JRS.6.063521
History: Received June 7, 2011; Revised November 30, 2011; Accepted February 15, 2012
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Abstract.  A novel shadow detection method for color remotely sensed images that satisfies requirements for both high accuracy and wide adaptability in applications is presented. This method builds on previously reported work investigating the shadow properties in both red/green/blue (RGB) and hue saturation value (HSV) color spaces. The method integrates several shadow features for modeling and uses a region growing (RG) algorithm and a perception machine (PM) of a neural network (NN) to identify shadows. To ensure efficiency of the parameters, first the proposed method uses a small number of shadow samples manually obtained from an input image to automatically estimate the necessary parameters. Then, the method uses the estimated threshold to binarize the hue map of the input image for obtaining possible shadow seeds and applies the RG algorithm to produce a candidate shadow map from the intensity channel. Subsequently, all of the hue, saturation, and intensity maps from the candidate shadow map are filtered with a corresponding band-pass filter, and the filtered results are input into the PM algorithm for the final shadow segmentation. Experiments indicate that the proposed algorithm has better performance in multiple cases, providing a new and practical shadow detection method.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Jiahang Liu ; Deren Li and Tao Fang
"Shadow detection for color remotely sensed images based on multi-feature integration", J. Appl. Remote Sens. 6(1), 063521 (Apr 23, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063521


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