Remote sensing image fusion based on fast discrete curvelet transform

Wavelet transform has the good characteristic of spatial and frequency locality, but it isnpsilat suitable for describing the signals, which have high dimensional singularities. Curvelet is one of new multiscale transform theories, which possess directionality and anisotropy, and it breaks some inherent limitations of wavelet in representing directions of edges in image. So when the curvelet transform is applied in image fusion, the characteristics of original images are taken better and implemented more easily. This paper tries fast discrete curvelet transform (FDCT) for image fusion of SAR (synthetic aperture radar) image and TM (thematic mapper) image. Then, visual result and statistical parameters are used to evaluate the result. The experimental results indicate that the FDCT-based fusion method can provide more detailed spatial information and simultaneously, preserves the richer spectral content than the conventional approach, such as the discrete wavelet transform (DWT) and the intensity-hue-saturation (IHS) transform.