*4.6. Discussion*

Experimental results demonstrate that the proposed method outperforms the other six hyperspectral pansharpening methods. The proposed method has a good performance in the spectral fidelity, since it always obtains an optimal SAM index. The HySure method has an excellent performance on the simulated images, but it performs badly on the real HS images. The proposed method performs well on the simulated and real hyperspectral images.

The superiority of the proposed method is owing to the employment of the weighted least squares filter and the intrinsic image decomposition. The WLS filter can make a proper compromise between sharpening and blurring, which improves the spatial quality of the fused image. The IID is an effective

technique to separate the HS image into the reflectance and illumination components, which plays an important role in reducing the spectral distortion.

A simple ye<sup>t</sup> effective fusion rule is introduced in this paper *α* determines the quantity of the finial injected spatial details and influences the fusion performance directly. We have tested the performance of the proposed method on various remote sensing images and many real satellite images with different *α* settings. We found that *α* = 0.1 always give the best performance. In future work, we plan to improve the performance of the proposed method by adaptively selecting parameter.
