摘要
鉴于应用单一主成分分析(PCA)或非下采样Contourlet(NSCT)变换进行多光谱和全色图像融合存在的问题,提出了一种2DPCA-NSCT变换图像融合算法。首先对多光谱图像各波段进行二维PCA变换,视其主成分为信号而少量非主成分为噪声予以忽略;然后对全色图像和第一主成分做NSCT分解,在频域对近似分量和多方向高频分量按不同的融合规则融合;最后通过NSCT反变换得到融合图像。实验结果表明,所提出的融合算法在保持PCA变换良好的空间分辨率的同时改善了其光谱失真的问题。
Aiming at the main problem in image fusion by single Principle Component Analysis （PCA） or Nonsubsampled Contourlet Transform, a novel image fusion algorithm based on 2DPCA-PC- NN transform is proposed. Firstly, 2DPCA is applied to multispectral image waveband. Its principle components are regarded as signal and its non-principle component is ignored because of being considered as noise. Secondly, the panchromatic mages and the first principle component are decomposed by non- subsampled Contourlet transform （NSCT）. The variance integration rules are used for the high frequent subband coefficients and the low-pass subband ones. Finally, the fusion image is achieved by inversing NSCT on the aforementioned subband coefficients. The simulation experiments show that the proposed method improves the spectral distortion as well as keeps the PCA transform good space resolution.
出处
《计算机工程与科学》
CSCD
北大核心
2013年第7期143-148,共6页
Computer Engineering & Science
基金
吉林省教育厅"十二五"科学技术研究项目(GH11307)
