基于波段指数的高光谱影像波段选择算法

为了去除高光谱影像的数据冗余，提高高光谱影像处理的精度和效率，提出了一种基于波段指数的高光谱影像波段选择算法。采用小波变换对高光谱图像数据进行去噪处理，依据联合偏度-峰度指数将波段进行分组，再根据波段指数的大小确定相对较小指数的波段，并将其作为冗余波段进行去除，从而得到最小波段集。结果表明，利用该波段集和全波段所选的端元是一致的，在不影响端元提取的前提下，最大程度地去除了冗余波段，而且该波段集与全波段的分类精度较接近。该算法在波段选择过程中具有可行性与有效性，为降低高光谱影像维数提供了一种帮助。

Band selection algorithm for hyperspectral images based on band index

In order to remove data redundancy of hyperspectral images, and improve the accuracy and efficiency of hyperspectral image processing, a band selection algorithm was proposed based on band index of hyperspectral images.Wavelet transform was used to deal with the noise of hyperspectral image data.Bands are divided into groups by using joint skewness-kurtosis figure, and the band was removed as a redundant band which was determined based on the size of band index.The set of the minimum bands was obtained in this way.The experimental results show that the endmember set selected by using the above bands is consistent with that selected by using all bands.The redundancy band is removed to the greatest extent without affecting the endmember extraction.The classification accuracy of the band set is close to that of all bands.The band selection algorithm is feasible and effective.The study provides help to reduce the dimension of hyperspectral images.