结合Gram-Schmidt变换的高光谱影像谐波分析融合算法

针对高光谱影像谐波分析融合(HAF)算法在影像融合时不顾及地物光谱曲线整体反射率这一缺陷,提出了结合Gram-Schmidt变换的高光谱影像谐波分析融合(GSHAF)改进算法。GSHAF算法可在完全保留融合前后像元光谱曲线波形形态的基础上,将高光谱影像融合简化为各像元光谱曲线的谐波余相组成的二维影像与高空间分辨率影像之间的融合。它是在原始高光谱影像光谱曲线被谐波分解为谐波余项、振幅和相位后,首先将其谐波余项与高空间分辨率影像进行GS变换融合,这样便可有效地修正融合后像元光谱曲线的反射率特征,随后再利用该融合影像与谐波振幅、相位进行谐波逆变换,完成高光谱影像谐波融合。本文最后利用Hyperion高光谱遥感影像与ALI高空间分辨率影像对GSHAF算法进行可行性分析,再以HJ-1A等卫星数据对其进行普适性验证,试验结果表明,GSHAF算法不仅可以完全地保留光谱曲线波形形态,而且融合后影像的地物光谱曲线反射率更接近真实地物。

Fusion Algorithm for Hyperspectral Remote Sensing Image Combined with Harmonic Analysis and Gram-Schmidt Transform

For the defect that harmonic analysis algorithm for hyperspectral image fusion(HAF)in image fusion regardless of spectral reflectance curves,the improved fusion algorithm for hyperspectral remote sensing image combined with harmonic analysis and Gram-Schmidt transform(GSHAF)is proposed in this paper.On the basis of completely retaining waveform of spectrum curve of fused image pixel,GSHAF algorithm can simplify hyperspectral image fusion to between the two-dimensional image by harmonic residual of each pixel spectral curve and high spatial resolution image.It is that the spectral curve of original hyperspectral image can be decomposed into harmonic residual,amplitude and phase,then GS transform with harmonic residual and high spatial resolution image,which can effectively amend spectral reflectance curve of fused image pixel.At last,this fusion image,harmonic amplitude and harmonic phase are inverse harmonic transformed.Finally,with Hyperion hyperspectral remote sensing image and ALI high spatial resolution image to analysis feasibility for GSHAF,then with HJ-1A and other satellite data to verify universality.The result shows that the GSHAF algorithm can not only completely retained the waveform of spectral curve,but also maked spectral reflectance curves of fused image more close to real situation.