11 January 2007 Object-oriented information extraction technology from QuickBird pan-sharpened images
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Proceedings Volume 6279, 27th International Congress on High-Speed Photography and Photonics; 62793L (2007) https://doi.org/10.1117/12.725360
Event: 27th International congress on High-Speed Photography and Photonics, 2006, Xi'an, China
Abstract
The high spatial resolution Remote Sensing image has richer information than the low or middle resolution image, such as structure and texture information. Traditional image classification technology which only uses spectral information of pixels is not suitable for the high resolution image. In order to make full use of the rich information, object-oriented thought is introduced into the high resolution information extraction. In contrast to traditional methods, the basic processing units of object oriented image analysis are image objects, and not single pixels. It could fully integrate spectral values and spatial information such as: shape, size and contextual relationship. The objective of this study is to extract kinds of information from QuickBird image of the urban area using the object-oriented information extraction approaches. Image processing includes geometric correction, HIS fusion, image segmentation and classification using the integration of fuzzy classification and the nearest neighbor (NN). 84.82% overall accuracy is achieved with this approach, while only 73.87% is achieved with traditional pixel-based method. It shows that object-oriented approach is promising in providing detailed and accurate information about the physical structure of urban areas from the high spatial image.
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Chunyan Zhou, Chunyan Zhou, Ping Wang, Ping Wang, Zhenyong Zhang, Zhenyong Zhang, Chengtao Qi, Chengtao Qi, Ying Wang, Ying Wang, } "Object-oriented information extraction technology from QuickBird pan-sharpened images", Proc. SPIE 6279, 27th International Congress on High-Speed Photography and Photonics, 62793L (11 January 2007); doi: 10.1117/12.725360; https://doi.org/10.1117/12.725360
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