针对一些遥感数据缺失蓝波段而无法进行真彩色影像合成的问题，提出一种模拟多光谱传感器真彩色影像的方法。将中分辨率成像光谱仪MODIS 地表反射率产品(MOD09)作为参考影像，经影像聚类分析得到具有代表性训练样本，并通过反向传播(BP)人工神经网络训练得到蓝波段与特征波段(绿/红/近红)间关系的非线性回归模型，该模型用于模拟Landsat TM/MSS 和SPOT-5 的蓝波段并最终合成真彩色影像。实验结果表明：BP 神经网络能够很好地模拟多光谱影像的蓝波段，并且能够在一定程度上去除蓝波段上的大气影响，从而可以得到较为理想的真彩色合成效果。研究成果进一步扩展了图-图遥感影像波段模拟模型的研究深度。

True color images can not be synthetized due to some remote sensing data missing blue band. A method of simulating true color remote sensing image is proposed. The MODIS land surface reflectivily product (MOD09) is used as reference image where to select pixel samples, and a non- linear regression analysis model is acquired through a back- propagation (BP) artificial neural network that used to fit the spectral reflectance relationship among the blue band and red, or green and near-infrared bands. Then Landsat TM/MSS and SPOT- 5 blue bands are simulated with the trained fitting model, and a natural- color image is acquired. The experimental result shows that using the BP neural network model, the blue band of a multispectral image is well simulated and even the atmospheric effect of the blue band is removed. Thus a more realistic and informative natural- color image is acquired. The research results further extend the research depth on remote sensing image band simulation model based on the image-image relationship.