CAJ | 학술논문

高光谱图像数据具有大量波段,波段之间的相关性较高,可以利用数据融合技术来降低其分析难度.提出了一种新颖的基于非采样Contourlet变换的高光谱图像融合算法.首先对高光谱数据进行特征图像提取;再将提取出的多幅特征图像分别进行非采样Contourlet变换,并按区域能量进行加权融合;最后对融合系数进行非采样Contourlet重构.实际的OMIS高光谱遥感图像融合的实验结果表明,所提基于非采样Contourlet变换的加权融合算法能够很好地保持图像的空间特性和光谱特性,且效果明显好于典型的小波变换和Contourlet变换的融合方法.
고광보도상수거구유대량파단,파단지간적상관성교고,가이이용수거융합기술래강저기분석난도.제출료일충신영적기우비채양Contourlet변환적고광보도상융합산법.수선대고광보수거진행특정도상제취;재장제취출적다폭특정도상분별진행비채양Contourlet변환,병안구역능량진행가권융합;최후대융합계수진행비채양Contourlet중구.실제적OMIS고광보요감도상융합적실험결과표명,소제기우비채양Contourlet변환적가권융합산법능구흔호지보지도상적공간특성화광보특성,차효과명현호우전형적소파변환화Contourlet변환적융합방법.
There are hundreds of bands in hyperspectral data and the bands are highly correlative. The difficulty of analysis could be- reduced by using fusion technology. A novel hyperspectral image fusion algorithm based on nonsubsampled Contourlet transform is proposed. Firstly, feature images extraction is applied to hyperspectral images; then, several feature images extracted are separately decomposed into multiresolution representation by nonsubsampled Contourlet transform and the coefficients are fused according to the weights which are calculated with the energy of the corresponding neighbor region. Finally, the fused coefficients are reconstructed by reverse nonsubsampled Contourlet transform. Experimental results for real OMIS hyperspectral images show that the proposed fusion algorithm of hyperspectral images based on nonsubsampled Contourlet transform could well retain spatial and spectral feature. In addition, it outperforms than the typical fusion algorithms such as wavelet transform and Contourlet transform.