An Efficient Method for Supervised Hyperspectral Band Selection

作者：Yang He^*; Du Qian; Su Hongjun; Sheng Yehua

来源：IEEE Geoscience and Remote Sensing Letters, 2011, 8(1): 138-142.

DOI：10.1109/LGRS.2010.2053516

• Band selection
• hyperspectral imagery

Band selection is often applied to reduce the dimensionality of hyperspectral imagery. When the desired object information is known, it can be achieved by finding the bands that contain the most object information. It is expected that these bands can provide an overall satisfactory detection and classification performance. In this letter, we propose a new supervised band-selection algorithm that uses the known class signatures only without examining the original bands or the need of class training samples. Thus, it can complete the task much faster than traditional methods that test bands or band combinations. The experimental result shows that our approach can generally yield better results than other popular supervised band-selection methods in the literature.

• 出版日期2011-1
• 单位南京师范大学