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A new approach to fusing PAN and MS remote sensing images with high fidelity of color

To improve the fusion effect of the PAN (Panchromatic) image and the MS (Multi-Spectral) image, this paper proposes a new fusion approach with high fidelity of color based on the combination of IHS and wavelet transformation. After the PAN image and the intensity component of MS image are decomposed respectively by wavelet transformation, lowfrequency sub-images are fused with a self-adaptive fusion rule based on the improved PCA (Principal Component Analysis), while the fusion rule of maximum of absolute values with consistent verification is used to fuse highfrequency sub-images. Then the intensity component of MS image is replaced by the merged data and the fused image is obtained by inverse IHS transform of the MS image. The subjective visual effect and the objective estimation indicate that the new method can preserve the color information very well. Compared to the traditional IHS and wavelet transform based algorithms, the color distortion of the proposed algorithm reduces 47.31% and 26.14% separately. In addition, compared to the weighted average fusion method of low-frequency coefficients and high-frequency coefficients substituted directly by high-frequency sub-images of the original PAN image, the color distortion of the introduced intelligent and self-adaptive fusion rule reduces 6.51% and 24.22% respectively.