[1] R Lu, T Shen, X Yang, . Infrared small moving target detection algorithm based on incremental inertial navigation information in high dynamic air to ground background (Invited). Infrared and Laser Engineering, 51, 20220191(2022).

[2] F Gao, X Yang, R Lu, . Anchor-free lightweight infrared object detection method (Invited). Infrared and Laser Engineering, 51, 20220193(2022).

[3] Yang X, Cheng S, Xi J. Aircraft Heterogeneous Scene Matching Guidance Technology[M]. Beijing: Science Press, 2016. （in Chinese）

[4] S Suri, P Reinartz. Mutual-information-based registration of terraSAR-X and ikonos imagery in urban areas. IEEE Transactions on Geoscience and Remote Sensing, 48, 939-949(2010).

[5] Y Fang, J Hu, C Du, et al. SAR-optical image matching by integrating Siamese U-Net with FFT correlation. IEEE Geoscience and Remote Sensing Letters, 19, 1-5(2021).

[6] Kwon O. Similarity measures f object matching in computer vision[D]. Engl: University of Bolton, 2016.

[7] D G Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60, 91-110(2004).

[8] Bay H, Tuytelaars T, Gool L V. SURF: Speeded up robust features[C]European Conference on Computer Vision, 2006: 407417.

[9] Detone D, Malisiewicz T, Rabinovich A. Superpoint: Selfsupervised interest point detection deion[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition Wkshops, 2018: 224236.

[10] Sarlin PE, Detone D, Malisiewicz T, et al. Superglue: Learning feature matching with graph neural wks[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2020: 49384947.

[11] Dusmanu M, Rocco I, Pajdla T, et al. D2: A trainable cnn f joint deion detection of local features[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2019: 80928101.

[12] Jiang W, Trulls E, Hosang J, et al. Cotr: Crespondence transfmer f matching across images[C]Proceedings of the IEEECVF International Conference on Computer Vision, 2021: 62076217.

[13] Sun J, Shen Z, Wang Y, et al. LoFTR: Detectfree local feature matching with transfmers[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 89228931.

[14] Efe U, Ince K G, Alatan A. Dfm: A perfmance baseline f deep feature matching[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 42844293.

[15] Goodfellow I, PougetAbadie J, Mirza M, et al. Generative adversarial s[C]Advances in Neural Infmation Processing Systems, 2014: 139144.

[16] T Chen, J Guo, X Han, . Visible and infrared image matching method based on generative adversarial model. Journal of Zhejiang University (Engineering Science), 56, 63-64(2022).

[17] J Zhao, D Yang, Y Li, et al. Intelligent matching method for heterogeneous remote sensing images based on style transfer. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 6723-6731(2022).

[18] Zhu J, Park T, Isola P, et al. Unpaired imagetoimage translation using cycleconsistent adversarial wks[C] Proceedings of the IEEE International Conference on Computer Vision, 2017: 22232232.

[19] X Li, Z Du, Y Huang, et al. A deep translation (GAN) based change detection network for optical and SAR remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 179, 14-34(2021).

[20] J Song, J Li, H Chen, et al. MapGen-GAN: A fast translator for remote sensing image to map via unsupervised adversarial learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 2341-2357(2021).

[21] Zhang R, Isola P, Efros A A, et al. The unreasonable effectiveness of deep features as a perceptual metric[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 586595.