SPATIALLY INFORMED SPECTRAL UNMIXING

被引:0
作者
Bongiorno, Daniel L. [1 ,2 ]
Fairley, Adam J. [2 ]
Williams, Stefan B. [1 ]
机构
[1] Univ Sydney, Australian Ctr Field Robot, Sydney, NSW, Australia
[2] Def Sci & Technol Org, Sydney, NSW, Australia
来源
2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2015年
关键词
Spectral Unmixing; Image Segmentation; Informed Unmixing; ISACS;
D O I
暂无
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
Spectral unmixing methods have traditionally relied on the plethora of information in the spectral domain to resolve sub pixel components. Several new methods have utilised the spatial information contained within the hyperspectral image, however these are limited to the spatial resolution of the sensor. In this work, spectral data is unmixed from a spectrometer co-registered with a high spatial resolution RGB camera. The image from the camera is segmented, informing the unmixing process about the number of materials and their abundance. This new algorithm has been titled Image Segmentation Assisted Constrained Spectral-unmixing (ISACS). This presents an intensive computational search. A method to reduce the computational complexity is covered in this work. The performance of these informed spectral unmixing methods are compared to literature methods.
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页数:4
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