An Improved Pca Fusion Method Based on Generalized Intensity–Hue–Saturation Fusion Technique

Abstract Among various image fusion methods, principal component analysis (PCA) technique is capable of quickly merging the massive volumes of data. For IKONOS imagery, PCA can yield satisfactory “spatial” enhancement but may introduce spectral distortion, appearing as a change in colors between compositions of resembled and fused multi-spectral bands. To solve this problem, a fast improved PCA fusion method based on Intensity–Hue–Saturation Fusion Technique with Spectral Adjustment is presented. The experimental results demonstrate that the proposed approach can provide better performance than the original PCA method both in processing speed and image quality.