**4. Conclusions and Future Work**

In this paper, a multi-spectral domain translation model based on conditional GAN architecture is proposed for remote sensing images of the earth background. To achieve multi-spectral domain adaptation, the model introduces feature maps of earth background and shared latent domain. In addition to adversarial loss, within domain reconstruction loss, cross domain reconstruction loss and latent matching loss are added to train the network. Besides, multi-spectral remote sensing images taken from a FY satellite are used as a dataset to test the effect of bidirectional translation between infrared band and visible band images. Compared with models such as pix2pix and cycleGAN, SDTGAN achieves more stable and accurate performance in translating spectral images at the pixel level, and simulating the surface structure and texture of clouds. In future work, we will explore a better structure for extraction, construction, and utilization of shared latent domain for spectral-domain translation, and extend it to other band combinations.

**Author Contributions:** Conceptualization, B.W. and J.W.; data curation, L.Z. and X.G., formal analysis, L.Z. and B.W.; funding acquisition, J.W. and X.W.; investigation, X.G., L.Z. and B.W.; methodology, J.W. and L.Z.; project administration, J.W. and X.W.; resources, J.W. and X.W.; software, L.Z. and X.G.; supervision, J.W.; validation, B.W. and L.Z.; visualization, L.Z. and X.G.; writing— original draft, B.W.; writing—review and editing, L.Z. and X.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work is supported by National Natural Science Foundation of China under Grant 62005205 and Natural Science Basic Research Program of Shaanxi (Program No. 2020JQ-331).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** No new data were created or analyzed in this study. Data sharing is not applicable to this article.

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