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

doi:10.11947/j.AGCS.2015.20140637

Abstract

Abstract: 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.

Key words: photogrammetry and remote sensing, hyperspectral remote sensing, harmonic analysis, Gram-Schmidt transform, image fusion

CLC Number:

P237

ZHANG Tao, LIU Jun, YANG Keming, LUO Wenshan, ZHANG Yuyu. Fusion Algorithm for Hyperspectral Remote Sensing Image Combined with Harmonic Analysis and Gram-Schmidt Transform[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(9): 1042-1047.

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