摘要
针对遥感图像融合问题,提出了一种基于残差的遥感图像融合新方法。该方法借助于主成分分析(principal component analysis,PCA),通过对多光谱图像的残差图像和全色图像的残差图像进行融合来恢复出多光谱图像的高分辨率残差图像,以实现多光谱图像和全色图像的融合。实验结果的主观视觉效果和客观统计参数分析都表明,新方法不仅较大地增强了融合图像的空间细节表现能力,而且很好地保留了多光谱图像的光谱信息,其性能优于现有的HIS(hue-intensity-saturation)变换融合方法、PCA融合方法和小波变换(wavelet transform,WT)融合方法。
For the problem of remote sensing image fusion, we propose a new scheme based on residual error in this paper. This scheme restores the high-resolution residual errors for muhispectral images by fusing the high-resolution residual error extracted from panchromatic image and the low-resolution residual errors extracted from muhispectral images based on principal component analysis (PCA). The assessment of experimental results from subjective visual effect and objective statistical analysis indicates that the proposed scheme has better performance in preserving the spectral characteristics of the multispectral images, while improving the spatial resolution, than the conventional image fusion methods such as the methods based on HIS (hue-intensity-saturation) transform, PCA, and wavelet transform(WT).
出处
《中国图象图形学报》
CSCD
北大核心
2007年第1期135-140,共6页
Journal of Image and Graphics
基金
国家自然科学基金项目(60672116
30370392)
国家重点基础研究项目(2001CB309400)
航天支撑技术基金项目(2004-1.3-03)
上海市自然科学基金项目(04ZR14018)
关键词
图像融合
主成分分析
高分辨率残差
低分辨率残差
image fusion, principal component analysis (PCA), high-resolution residual error, low-resolution residual error