基于带参考信号独立分量分析的高光谱图像目标探测

提出了一种用于高光谱图像目标探测的预处理方法,目的是提高目标光谱的准确性,进而提高有监督目标探测算法的精度.该方法将实验室或野外获取的目标光谱作为参考信号,利用带参考信号的独立分量分析方法,从图像中提取出与参考信号相关性最大的独立分量作为新的目标光谱.仿真和实际高光谱数据的实验结果表明,所提出的方法能较大提高目标光谱的准确性,从而较大提高目标探测算法的精度.

Target detection in hyperspectral imagery based on independent component analysis with references

A new preprocessing method used for target detection in hyperspectral imagery was proposed. This preprocessing method can increase target spectra accuracy, so the performance of the target detection methods can be improved. By using the target spectra gotten from the laboratory and field as references, the proposed method extracts independent components, which are the closest to the references, from the hyperspectral imagery by means of independent component analysis with references (ICA-R). Then, these independent components are used as target spectra in the following supervised target detection methods. Experimental results on both simulated and real hyperspectral data demonstrate that the proposed method can get more accurate target spectra, which obtains much better performance of target detection.