Paper
23 November 2011 Shadow detection of the high-resolution remote sensing image based on pulse coupled neural network
Wei Huang, Yu Xiao, Shan Lu
Author Affiliations +
Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80060Q (2011) https://doi.org/10.1117/12.901852
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
Traditional shadow detection methods are usually detected shadow areas by the single threshold in shadow feature map. This leads to the detection results susceptible to affect by noise, and some special target (high-bright objects and green vegetation etc.) susceptible to misdetection. In this paper, a shadow detection method is proposed based on pulse coupled neural network (PCNN). The model can ignore small differences of pixels values in one area, because the network output is not only associated with the pixel brightness but also associated with pixel spatial location. Firstly, a new shadow feature map is build. Then PCNN model is applied to get optimal detection result with max entropy. The experimental results showed that the proposed model performed better than the single threshold models.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Huang, Yu Xiao, and Shan Lu "Shadow detection of the high-resolution remote sensing image based on pulse coupled neural network", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060Q (23 November 2011); https://doi.org/10.1117/12.901852
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Cited by 1 scholarly publication.
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KEYWORDS
RGB color model

Neurons

Remote sensing

Image processing

Sensors

Neural networks

Vegetation

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