In this paper

after several-hundred times of comparing calculation of the hyper-spectral and Quickbird data in two land utilization survey areas

The Sym4 and Db2 are determined to be the best wavelet function in the curvature-wave transformation at last. Two hyper-spectral remote-sensing image fusion algorithms

i.e.

weighted method and selected method

are given based on the curvature-wave transformation. And then the more precise fusion images are provided. In one research area

the hyper-spectral remote-sensing fusion image is benefited for the land typing and image discrimination after the images to resolve son

ridge-wave transformation

some fusions

and their inversion transformation of the hyper-spectral data. In the other research area

except for the curvature-wave transformation

the remote-sensing image matching of the hyper-spectral and the Quickbird data is finished by calculation of quadratic equation

and the fusion image of the curvature-wave transformation is better than that of wavelet transformation

and similar to the Brovey fusion image and slightly inferior of PCA fusion image after the appraising by observation

information entropy and relation analysis. It is suggested that the hyper-spectral remote-sensing image fusion algorithm can provide more precise information for the land utilization survey based on the curvature-wave transformation.