1. [1] X. Jiang, J. Ma, G. Xiao, Z. Shao, and X. Guo, "A review of multimodal image matching: Methods and applications," Information Fusion, vol. 73, pp. 22-71, 2021. [DOI:10.1016/j.inffus.2021.02.012]

2. [2] X. Meng, H. Shen, H. Li, L. Zhang, and R. Fu, "Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges," Information Fusion, vol. 46, pp. 102-113, 2019. [DOI:10.1016/j.inffus.2018.05.006]

3. [3] I. Amro, J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "A survey of classical methods and new trends in pansharpening of multispectral images," EURASIP Journal on Advances in Signal Processing, vol. 2011, no. 1, pp. 1-22, 2011. [DOI:10.1186/1687-6180-2011-79]

4. [4] A. Arienzo, G. Vivone, A. Garzelli, L. Alparone, and J. Chanussot, "Full-resolution quality assessment of pansharpening: Theoretical and hands-on approaches," IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 3, pp. 168-201, 2022. [DOI:10.1109/MGRS.2022.3170092]

5. [5] Z.-R. Jin, Y.-W. Zhuo, T.-J. Zhang, X.-X. Jin, S. Jing, and L.-J. Deng, "Remote sensing pansharpening by full-depth feature fusion," Remote Sensing, vol. 14, no. 3, p. 466, 2022. [DOI:10.3390/rs14030466]

6. [6] G. Khademi and H. Ghassemian, "A multi-objective component-substitution-based pansharpening," in 2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA), 2017: IEEE, pp. 248-252. [DOI:10.1109/PRIA.2017.7983056]

7. [7] S. Wady, Y. Bentoutou, A. Bengermikh, A. Bounoua, and N. Taleb, "A new IHS and wavelet based pansharpening algorithm for high spatial resolution satellite imagery," Advances in space research, vol. 66, no. 7, pp. 1507-1521, 2020. [DOI:10.1016/j.asr.2020.06.001]

8. [8] V. P. Shah, N. H. Younan, and R. L. King, "An efficient pan-sharpening method via a combined adaptive PCA approach and contourlets," IEEE transactions on geoscience and remote sensing, vol. 46, no. 5, pp. 1323-1335, 2008. [DOI:10.1109/TGRS.2008.916211]

9. [9] A. Garzelli, F. Nencini, and L. Capobianco, "Optimal MMSE pan sharpening of very high resolution multispectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 46, no. 1, pp. 228-236, 2007. [DOI:10.1109/TGRS.2007.907604]

10. [10] G. Vivone, "Robust band-dependent spatial-detail approaches for panchromatic sharpening," IEEE transactions on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 6421-6433, 2019. [DOI:10.1109/TGRS.2019.2906073]

11. [11] B. Aiazzi, S. Baronti, and M. Selva, "Improving component substitution pansharpening through multivariate regression of MS $+ $ Pan data," IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 10, pp. 3230-3239, 2007. [DOI:10.1109/TGRS.2007.901007]

12. [12] R. Restaino, M. Dalla Mura, G. Vivone, and J. Chanussot, "Context-adaptive pansharpening based on image segmentation," IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 2, pp. 753-766, 2016. [DOI:10.1109/TGRS.2016.2614367]

13. [13] C. A. Laben and B. V. Brower, "Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening," ed: Google Patents, 2000.

14. [14] J. Choi, K. Yu, and Y. Kim, "A new adaptive component-substitution-based satellite image fusion by using partial replacement," IEEE transactions on geoscience and remote sensing, vol. 49, no. 1, pp. 295-309, 2010. [DOI:10.1109/TGRS.2010.2051674]

15. [15] C. Jin, L.-J. Deng, T.-Z. Huang, and G. Vivone, "Laplacian pyramid networks: A new approach for multispectral pansharpening," Information Fusion, vol. 78, pp. 158-170, 2022. [DOI:10.1016/j.inffus.2021.09.002]

16. [16] K. Yaghoubi, A. Safdarinezhad, and M. Jafari, "A method for determining the optimum parameter of the soft filters to image fusion in the frequency domain," Journal of Space Science and Technology, vol. 14, no. 3, pp. 23-37, 2021.

17. [17] F. Palsson, J. R. Sveinsson, M. O. Ulfarsson, and J. A. Benediktsson, "Model-based fusion of multi-and hyperspectral images using PCA and wavelets," IEEE transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2652-2663, 2014. [DOI:10.1109/TGRS.2014.2363477]

18. [18] N. Ahmadian, A. Sedaghat, and N. Mohammadi, "Performance evaluation of three deep learning models in building footprint extraction from aerial and satellite images," Engineering Journal of Geospatial Information Technology, vol. 11, no. 1, pp. 105-123, 2023. [DOI:10.61186/jgit.11.1.105]

19. [19] G. Masi, D. Cozzolino, L. Verdoliva, and G. Scarpa, "Pansharpening by convolutional neural networks," Remote Sensing, vol. 8, no. 7, p. 594, 2016. [DOI:10.3390/rs8070594]

20. [20] X. Fu, W. Wang, Y. Huang, X. Ding, and J. Paisley, "Deep multiscale detail networks for multiband spectral image sharpening," IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 5, pp. 2090-2104, 2020. [DOI:10.1109/TNNLS.2020.2996498]

21. [21] P. Wang and E. Sertel, "Channel-spatial attention-based pan-sharpening of very high-resolution satellite images," Knowledge-Based Systems, vol. 229, p. 107324, 2021. [DOI:10.1016/j.knosys.2021.107324]

22. [22] Q. Liu, H. Zhou, Q. Xu, X. Liu, and Y. Wang, "PSGAN: A generative adversarial network for remote sensing image pan-sharpening," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 12, pp. 10227-10242, 2020. [DOI:10.1109/TGRS.2020.3042974]

23. [23] F. Ozcelik, U. Alganci, E. Sertel, and G. Unal, "Rethinking CNN-based pansharpening: Guided colorization of panchromatic images via GANs," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 3486-3501, 2020. [DOI:10.1109/TGRS.2020.3010441]

24. [24] H. Wu, L. Zhang, and J. Ma, "Remote sensing image super-resolution via saliency-guided feedback GANs," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2020. [DOI:10.1109/TGRS.2020.3042515]

25. [25] B. Liu et al., "Saliency-guided remote sensing image super-resolution," Remote Sensing, vol. 13, no. 24, p. 5144, 2021. [DOI:10.3390/rs13245144]

26. [26] A. Sedaghat and N. Mohammadi, "Illumination-robust remote sensing image matching based on oriented self-similarity," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 153, pp. 21-35, 2019. [DOI:10.1016/j.isprsjprs.2019.04.018]

27. [27] W. T. Freeman and E. H. Adelson, "The design and use of steerable filters," IEEE Transactions on Pattern analysis and machine intelligence, vol. 13, no. 9, pp. 891-906, 1991. [DOI:10.1109/34.93808]

28. [28] D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International journal of computer vision, vol. 60, no. 2, pp. 91-110, 2004. [DOI:10.1023/B:VISI.0000029664.99615.94]

29. [29] Z. Wang and A. C. Bovik, "A universal image quality index," IEEE signal processing letters, vol. 9, no. 3, pp. 81-84, 2002. [DOI:10.1109/97.995823]

30. [30] R. H. Yuhas, J. W. Boardman, and A. F. Goetz, "Determination of semi-arid landscape endmembers and seasonal trends using convex geometry spectral unmixing techniques," in JPL, Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 1: AVIRIS Workshop, 1993.

31. [31] S. Lolli, L. Alparone, A. Garzelli, and G. Vivone, "Haze correction for contrast-based multispectral pansharpening," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 12, pp. 2255-2259, 2017. [DOI:10.1109/LGRS.2017.2761021]

32. [32] A. Garzelli, B. Aiazzi, L. Alparone, S. Lolli, and G. Vivone, "Multispectral pansharpening with radiative transfer-based detail-injection modeling for preserving changes in vegetation cover," Remote Sensing, vol. 10, no. 8, p. 1308, 2018. [DOI:10.3390/rs10081308]

33. [33] R. Restaino, G. Vivone, M. Dalla Mura, and J. Chanussot, "Fusion of multispectral and panchromatic images based on morphological operators," IEEE Transactions on Image Processing, vol. 25, no. 6, pp. 2882-2895, 2016. [DOI:10.1109/TIP.2016.2556944]

34. [34] A. Sedaghat and N. Mohammadi, "Uniform competency-based local feature extraction for remote sensing images," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 135, pp. 142-157, 2018. [DOI:10.1016/j.isprsjprs.2017.11.019]