SUPER-RESOLUTION OF HYPERSPECTRAL IMAGERY USING COMPLEX RIDGELET TRANSFORM.

In this paper, a novel super-resolution method for hyperspectral imagery is proposed by using complex ridgelet transform. A Radon transform is first applied to each band image of a datacube to be enhanced to obtain the Radon slices, and then a 1D dual-tree complex wavelet transform is conducted along each Radon slice to generate coefficients of the complex ridgelet transform. The ordinary ridgelet transform or the finite ridgelet transform (FRIT), however, uses the 1D scalar wavelet transform instead of the dual-tree complex wavelet transform along each Radon slice. The reason why the dual-tree complex wavelet is adopted in this paper is because it has the property of approximate shift invariance, which is very important in image super-resolution. Experiments are conducted in this paper to demonstrate the advantages of the proposed method over the wavelet super-resolution, the FRIT image fusion, and the principal component analysis fusion. [ABSTRACT FROM AUTHOR]