Active Contours with Edges: Combining Hyperspectral and Grayscale Segmentation

被引:0
|
作者
Chen, Alex [1 ]
机构
[1] Univ N Carolina, Chapel Hill, NC 27515 USA
关键词
M ultiple Class Segmentation; Hyperspectral Imagery; Endmember Selection; Split Bregman; Anomaly Detection; Fused Segmentation;
D O I
10.1117/12.974445
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this work, we introduce a method to segment hyperspectral images using a Chan-Vese framework. We utilize a modified l(2) distance especially well-suited for hyperspectral classification problems. This distance considers spectral signal shape rather than illumination for the classification of objects. The practicality of multiple phase segmentation in this application is also demonstrated. We then use a high spatial resolution grayscale or color image and a high spectral, but low spatial resolution hyperspectral image to produced a fused segmentation result that is more accurate than segmentation on either image alone. Lastly, we show that the algorithm also gives a natural method for endmember selection and apply this result to anomaly detection.
引用
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页数:9
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