摘要
为使融合后的图像在尽可能保持原图像光谱信息的同时,有效提高空间细节信息,提出了一种新的基于非下采样Contourlet变换(NSCT)和主成分分析(PCA)的全色图像和多光谱图像融合算法.对多光谱图像进行PCA变换得到主元分量,将处理后的主元分量与全色图像进行NSCT分解,针对低频子带系数选择提出了一种基于窗口与局部方差相结合的融合策略;在高频子带系数选择上,提出了基于区域线性相关测定的融合策略.进行非下采样Contourlet逆变换和PCA逆变换,得到具有高空间质量的多光谱图像.实验结果表明,提出的算法在保留光谱信息和提高空间细节信息的综合性能上有所提高,能够取得较好的融合效果.
In order to preserve possibly the spectral information and enhance synchronously the spatial detail information for the fused image, a novel panchromatic and multispectral image fusion algorithm based on nonsubsampled contourlet transform （NSCT） and principal component analysis （PCA） was proposed. The principal component was obtained by PCA transformation for multispectral image. The NSCT decomposition was performed for the processed principal component and panchromatic image. The fusion strategy combined window with local variance was proposed for the low-frequency band coefficient choice. And the fusion strategy based on regional linear relativity measurement was proposed for the high-frequency band coefficient choice. A fused multispectral image with high spatial quality was obtained through performing inverse NSCT and PCA transforms. The experimental results show that the proposed fusion scheme can improve the comprehensive properties in preserving the spectral information and improving the spatial detail information, and achieve better fusion effect.
出处
《沈阳工业大学学报》
EI
CAS
2011年第3期308-314,共7页
Journal of Shenyang University of Technology
基金
国家自然科学基金资助项目(61077079)
哈尔滨市优秀学科带头人基金资助项目(2009RFXXG034)
