摘要
根据高光谱波段选择的基本准则,将子空间划分、基于矩阵模式的高光谱波段选择方法(BSMM)、波段指数(OIF)三者相结合,提出了一种新的波段选择方法 ABO。该方法首先根据各波段之间的相关性进行子空间划分;然后,在全波段范围内利用基于矩阵模式的高光谱波段选择方法得到单一量化指标W,选出各子空间中量化指标W取最大值所对应的波段;其次,针对已选波段计算任意3个波段的波段指数(OIF),波段指数最大值所对应的3个波段即为所选波段;最后,利用AVIRIS真实高光谱数据进行仿真实验,对所选3个波段进行RGB合成与HSV变换以及RX异常检测,通过与以往波段选择方法进行对比验证了所提方法的有效性。
Based on the principles of band selection, in this paper, a new method of band selection, named AN）, was proposed by combing the subspace partition, the band selection method based on matrix mode（BSMM）, and the optimum index factor（OIF）. In ABO, firstly, based on the correlation of bands, all bands are divided into different subspaces. Then, the index ＂W＂ is gotten through the method of BSMM, and only one band is seclected in each suhspace, in which the seclected band has the maximal ＂W＂. After this, the OIF from each three bands of the seclected is calculated. At last, the new method is tested by the real hyperspectral remote sensing imagery, and the three seclected bands is carried on RGB synthesize, HSV transformation and the RX anomaly detection. The results show that the proposed method has the best effect.
出处
《计算机科学》
CSCD
北大核心
2015年第B11期162-165,168,共5页
Computer Science
基金
国家自然科学基金(61271353)
安徽省自然科学基金(KY11070)资助
关键词
高光谱
波段选择
相关系数
子空间
H yperspectral, Band selection, Correlation, Subspace
