基于非下采样Contourlet变换和PCA的遥感图像融合

Ding Li
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引用次数: 7

摘要

提出了一种基于NSCT和PCA的全色和多光谱图像融合新方法。通过对多光谱图像进行主成分分析,得到第一主成分。然后融合经NSCT变换后的全色图像的第一主分量和低频系数。将反NSCT进行的融合数据替换为第一主分量,并进行反PCA变换。实验结果表明,与传统的HSI、PCA和NSCT相比,该方法能有效地保留光谱信息并改善空间信息,具有更好的主观视觉效果。
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Remote Sensing Image Fusion Based on Nonsubsampled Contourlet Transform and PCA
This paper proposes a new method of fusing panchromatic and multispectral images based on NSCT and PCA. The first principle component is obtained by applying PCA on multispectral images. Then fusing the first principle component and low frequent coefficients of panchromatic images after transformed by NSCT. Substituting the fusion data performed by inverse NSCT for the first principle component and applying the inverse PCA transform. Experimental results show that the proposed method can effectively preserve spectral information and improve spatial information than traditional HSI, PCA and NSCT, and has better subjective visual effect.
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