Paper
3 November 2010 A new method of extracting shape features from IKONOS imagery based on Fourier Descriptor: an application to object-oriented classification
Wei Wan, Xuezhi Feng, Pengfeng Xiao, Limin Zhao
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Abstract
Shape is an important visual feature of very high-resolution satellite data. Fourier Descriptor (FDs) was introduced in this paper as a new method to extract and represent objects' shape features of IKONOS imagery and a 5-dimensional (5- D) feature-vector was proposed as a shape parameter. A classification model was established based on K-means clustering algorithm, the 5-D feature-vector was taken as discrimination variable together with the mean gray values. The results showed that when involving the shape feature-vector into the classification model, the overall classification accuracy was 82.4% with 84.6% producer accuracy of roads. So it was confirmed a feasible way to represent shape features of remotely sensed imagery based on FDs.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Wan, Xuezhi Feng, Pengfeng Xiao, and Limin Zhao "A new method of extracting shape features from IKONOS imagery based on Fourier Descriptor: an application to object-oriented classification", Proc. SPIE 7840, Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality, 78401I (3 November 2010); https://doi.org/10.1117/12.872947
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KEYWORDS
Image segmentation

Roads

Buildings

Image classification

Earth observing sensors

High resolution satellite images

Image resolution

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