Hyperspectral image classification by collaboration of spatial and spectral information

Yu-zhou Yan; Yongqiang Zhao; Hui-feng Xue; Xiao-dong Kou; Yuanzheng Liu

doi:10.1117/12.839633

5 August 2009 Hyperspectral image classification by collaboration of spatial and spectral information

Yu-zhou Yan, Yongqiang Zhao, Hui-feng Xue, Xiao-dong Kou, Yuanzheng Liu

Proceedings Volume 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications; 73834B (2009) https://doi.org/10.1117/12.839633
Event: International Symposium on Photoelectronic Detection and Imaging 2009, 2009, Beijing, China

Abstract

The classification of hyperspectral image data has drawn much attention in recent years. Consequently, it contains not only spectral information of objects, but also spatial arrangement of objects. The most established Hyperspectral classifiers are based on the observed spectral signal, and ignore the spatial relations among observations. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. To combine the spectral and spatial information in the classification process, in this paper, a Multidimensional Local Spatial Autocorrelation (MLSA) is proposed for hyperspectral image data. Based on this measure, a collaborative classification method is proposed, which integrates the spectral and spatial autocorrelation during the decision-making process. The trials of our experiment are conducted on two scenes, one from HYDICE 210-band imagery collected over an area that contains a diverse range of terrain features and the other is toy car hyperspectral image captured at Instrumentation and Sensing Laboratory (ISL) at Beltsville Agricultural Research Center. Quantitative measures of local consistency (smoothness) and global labeling, along with class maps, demonstrate the benefits of applying this method for unsupervised and supervised classification.

Citation Download Citation

Yu-zhou Yan, Yongqiang Zhao, Hui-feng Xue, Xiao-dong Kou, and Yuanzheng Liu "Hyperspectral image classification by collaboration of spatial and spectral information", Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73834B (5 August 2009); https://doi.org/10.1117/12.839633

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KEYWORDS

Hyperspectral imaging

Image classification

Image segmentation

Image fusion

Remote sensing

Image processing

Agriculture

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