基于主成分分析的遥感图像模拟真彩色融合法

Remote-sensing Simulative True-color Fusion Method Based on Principal Components

对不同空间分辨率、时间分辨率和波谱分辨率的遥感图像进行综合、高效的利用,是遥感应用的关键问题之一。基于主分量变换法,提出了基于主成分分析的模拟真彩色融合法。该方法不仅具有主成分分析融合法的光谱波段选择灵活和光谱信息损失小等优点,同时该方法还可获得逼真的自然色彩的融合图像,提高了图像的融合效果。利用QuickBird全色和多光谱数据进行了试验,并与色彩空间变换法(IHS)、比值变换融合法和乘积变换法等传统方法,在定性和定量两个方面进行了比较分析。结果表明,新方法很好的保留了多光谱影像的光谱信息,提高了空间细节的表现能力,是一种有效实用的遥感图像融合方法。

The efficient integration of remote-sensing images with multiple spatial, temporal and spectrum resolution was a key of remote-sensing application. This paper presented a new remote sensing image fusion method based on Principal Component Analysis, which had the Principal Components Analysis advantage of choosing the spectrum bands flexibly and reserving much spectrum information. At the same time it got the close to natural color fusion image and increased the image fusion effect. It tested the method using the QuickBird high spatial pan and multi-spectral data, analysed and compared it with the IHS, Brovey, Multiplicative and etes in qualitative and quantificational aspects. The result images showed the new method not only reserved the spectrum information very well, but also improved details. It was an effective and applied fusion method.