CAJ | 학술논문

针对传统的PCA变换遥感图像融合技术会丢失部分多光谱遥感图像的光谱信息变量，从而造成光谱图像信息域的失真问题提出了基于PCA变换与小波变换的遥感图像融合方法。该方法首先提出多光谱遥感图像信息域的各波段相关矩阵的特征值变量和特征向量域，对多光谱图像进行主分量的变换，继而求得各主分量变量；然后将非灰度图像与多光谱图像信息域的首个主分量做直方图信息变量的匹配，利用小波变换融合方法来实现多光谱图像信息变量的首个主分量与非灰度图像的融合，其多光谱图像的首个主分量被融合结果来替代；最后对多光谱图像信息变量的3个主分量变量作逆主分量变换得到所需的最终融合图像信息域。仿真实验表明，该方法使最终融合的图像在多光谱信息的保持与空间细节信息的增强两个方面的综合性能均得到提高。
침대전통적PCA변환요감도상융합기술회주실부분다광보요감도상적광보신식변량，종이조성광보도상신식역적실진문제제출료기우PCA변환여소파변환적요감도상융합방법。해방법수선제출다광보요감도상신식역적각파단상관구진적특정치변량화특정향량역，대다광보도상진행주분량적변환，계이구득각주분량변량；연후장비회도도상여다광보도상신식역적수개주분량주직방도신식변량적필배，이용소파변환융합방법래실현다광보도상신식변량적수개주분량여비회도도상적융합，기다광보도상적수개주분량피융합결과래체대；최후대다광보도상신식변량적3개주분량변량작역주분량변환득도소수적최종융합도상신식역。방진실험표명，해방법사최종융합적도상재다광보신식적보지여공간세절신식적증강량개방면적종합성능균득도제고。
The traditional PCA image fusion can produce multi-spectral image information variable loss in remote image fusion. Aim to it, a new algorithm of remote sensing image fusion based on PCA and wavelet transform was proposed in this paper. Firstly, principal component transformation for multi-spectral image was performed by eigenvalues and eigenvectors in each wave band. Secondly, the first non principal component of non-gray image and multi spectral image were matched in histogram information. Finally, inverse PCA transform was carried out for three principal components to obtain the desired fusion image. Experimental results show the proposed algorithm does not only maintain multi spectral information but also enhanced the processed image details, and the processed image has better subjective visual effect and objective quantitative indicators.