**5. Conclusions**

Hyperspectral pansharpening is an important subdivision of remote sensing image processing. A novel hyperspectral pansharpening method based on IID and WLS filter has been presented in this paper. The proposed method first obtains the spatial information of the *P* image with a weighted least squares filter, in which the LOG enhancement algorithm was used for the spatial enhancement. Then, the illumination component which is considered the spatial information of the HS image is estimated with the intrinsic image decomposition technique. The fused image can be obtained by injecting the detail map into each band of the deblurred interpolated HS image. The final injected spatial information takes full account of the *P* and the HS images. The impact of data independence can be eliminated. The existing problem of the CS and MRA-based fusion methods can be well solved by the combination of an IID technique and a WLS filter. Experiments conducted on six synthetic and real hyperspectral datasets demonstrated that the proposed method performs better than the state-of-the-art fusion methods as well as the CS and MRA-based fusion methods in terms of visual inspection and objective analysis.

**Acknowledgments:** This work was supported by NSFC (No. 61372069), National Defense Pre-research Foundation, SRF for ROCS, SEM (JY0600090102), "111" project (No. B08038) and the Fundamental Research Funds for the Central Universities.

**Author Contributions:** Wenqian Dong drafted the manuscript; Wenqian Dong, Song Xiao, and Yunsong Li conceived and designed the experiments; Wenqian Dong and Jiahui Qu performed the experiments; Wenqian Dong and Song Xiao analyzed the data; Yunsong Li and Jiahui Qu modified the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.
