Three-Dimensional Empirical Mode Decomposition Based Hyperspectral Band Selection Method

Hyperspectral technology is a huge leap of remote sensing technology, however, how to make full use of its rich information is a difficult problem. A novel hyperspectral band selection method based on 3D empirical mode decomposition (3D-EMD) is proposed by constructing the upper approximation and the lower approximation of the whole image. The hyperspectral image (HSI) is decomposed into a set of tridimensional intrinsic mode functions (TIMFs) and bands are selected from the HSI using each TIMF based on optimum index factor (OIF). These bands are combined into a band combination. Experimental results demonstrate that the proposed method yields improved decomposition performance on the HSI and increases classification accuracy.