Study of urban objects stepping classification based on spectral feature

Jingxue Wang; Weidong Song

doi:10.1117/12.749076

15 November 2007 Study of urban objects stepping classification based on spectral feature

Jingxue Wang, Weidong Song

Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678712 (2007) https://doi.org/10.1117/12.749076
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Urban is a kind of very complex living space, and includes many and many different objects. For urban imagery, it is hardly to get a satisfied classification result utilizing any kind of single classification method. Aiming at this problem, this paper adopts a kind of classification method based on stepping masking principle using the parallel-pipeline classification and the improved FCM method. With this classification principle, it not only enhances the computation efficiency of classification, but also realizes the accurate and reasonable classification to the different kinds of urban objects. Finally this paper evaluates the precision of classification results using the confusion matrix and the Kappa coefficient separately. Analyzing from the classification effect and precision, this algorithm can satisfy the requirement of classification in different level or the thematic mapping.

Citation Download Citation

Jingxue Wang and Weidong Song "Study of urban objects stepping classification based on spectral feature", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678712 (15 November 2007); https://doi.org/10.1117/12.749076

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