High Resolution Remote Sensing Image Fusion Method Based on Curvelet and HCS

To obtain high spatial and spectral resolution image, we propose a novel method of high resolution remote sensing image fusion based on the second generation curvelet transform and hyperspherical color space transform which can fuse n-band multispectral and panchromatic images. The GF-1 satellite images are used as experimental data, and the fused image are quantitatively analyzed according to the mean, the standard deviation, the correlation coefficient, the information entropy and the average gradient. The results show that the proposed method has better performance than other fusion methods such as Principal Component Analysis, Gramm-Schmidt, and Hyperspherical Color Sharpening.