Fusion of panchromatic image and multi-spectral image based on SVR and Bayesian method

The fusion images with high spatial resolution and high spectral resolution can be obtained by fusing panchromatic images and multi-spectral images. Support vector value contourlet transform constructed by using support vector regression model was used to decompose source images at multi-scale, multi-direction and multi-resolution. The algorithm of fusing panchromatic image and multi-spectral image was derived at different levels by using Bayesian method. By utilizing the strong learning ability of support vector regression and the relationship of multi-spectral image with panchromatic image, the super-resolved multi-spectral image was reconstructed to resolve the problem of coincident resolution of images to be fused. Experimental results show that the fused image obtained by the method not only has high spatial resolution, but also preserves the spectral characteristics of the multi-spectral images. The fusion performance of the method is better than traditional image fusion methods.