摘要
针对多光谱遥感影像和全色遥感影像,提出了一种基于小波包变换的遥感影像融合方法。新方法首先对多光谱遥感影像进行PCA变换;其次对多光谱遥感影像的第一主分量和全色遥感影像进行小波包变换;然后保留多光谱影像第一主分量的低频近似分量,融合它们的高频细节分量;最后,做小波包反变换,得到新的多光谱遥感影像第一主分量,再做PCA反变换,得到新的多光谱遥感影像。与PCA变换融合方法、IHS变换融合方法和小波变换融合方法等方法在主观视觉效果分析和客观统计参数两方面做了比较,新方法是有效的,不仅较大地增强了结果影像的空间细节表现能力,而且很好地保留了多光谱影像的光谱信息。
Remote sensing image fusion is becoming widely used in object recognition because of complementary nature of images from different sensors. The result of image fusion is a single image which is more suitable for human and machine perception or further image processing. In this paper, a new remote\|sensing image fusion method based on wavelet packet transform (WPT) to fusion a multi\|spectral image and a panchromatic image is studied. Firstly, the multi\|spectral image is transformed with PCA, and three principal components can be obtained. Secondly, the first principal component of the multi\|spectral image and panchromatic image are transformed with wavelet packet transform. Thirdly, their high\|frequency coefficients are combined efficiently, while the low\|frequency coefficients of the first principal component of the multi\|spectral image are preserved. Fourthly, the first principal component of the multi\|spectral image is transformed with inverse wavelet packet transform. Finally, the fusioned image is obtained by inverse PCAT. Visual result and statistical parameters indicate that the performance of our new method is efficient comparing with those of PCAT (principal component analysis Transform)\|based fusion method, IHST (Intensity\|Hue\|Saturation transform)\|based one, and WT (wavelet transform) \|based one. It not only enhances spatial detail information of the result image largely, but also preserves spectral information of the original multispectral image well.
出处
《遥感技术与应用》
CSCD
2003年第4期248-253,共6页
Remote Sensing Technology and Application
关键词
遥感影像融合
主分量分析
IHS变换
小波包变换
小波变换
Remote sensing image fusion, Principal component analysis, IHS transform, Wavelet transform, Wavelet packet transform
