针对已有遥感影像模拟方法难以在影像光谱维上扩展的不足, 提出了一种基于地物波谱学习的遥感影像波段模拟方法.以地物波谱库作为先验知识,通过支持向量机拟合地物在不同观测波段范围内反射率之间的复杂非线性关系, 进而在多光谱遥感影像已有波段的基础上模拟一个新的波段影像.通过模拟TM红波段影像的实验, 证明本方法能较为准确地模拟出真实的光谱影像, 其模拟结果可靠.进一步将该方法应用于模拟IRS真彩色影像, 验证了本方法的实用性.本方法能够有效地解决多光谱影像波段缺损的问题, 并在一定程度上可解决较高空间分辨率遥感影像光谱维的不足, 为建立地物波谱与遥感像元波谱的定量联系提出了新的思路.

A method for remote sensing image band simulation based on ground-object spectral features study by support vector machine(SVM) was proposed, since the existing simulation methods had difficulties in the spectrum bands extension. By taking spectral features into account as a priori knowledge and according to the study of the complicated and nolinear relationships among ground-object spectra in different bands by SVM, a new band image was simulated on the basis of the existing sensor bands of multi-spectral remote sensing images. Based on TM red band simulation experiments, it is confirmed that the method can precisely simulate the real spectral images and the simulation results are reliable. Furthermore, the method was used to simulating IRS true-color experiments. The results verify that it is a practical method to reconstruct the missing bands of multi-spectral image. The method effectively resolves the band defection problem of multi-spectral images, and it also resolves the spectral bands deficiency of high spatial resolution remote sensing image to some extent. The method puts forward a new idea for establishing links between ground-object spectrum and remote sensing pixel spectrum.