Colorizing sentinel-1 SAR images using a variational autoencoder conditioned on Sentinel-2 imagery

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 42, Issue 2, 2018, Pages 1045-1051

  Schmitt, M ^a   Hughes, L H ^a   Korner M ^a   Zhu, X X ^a,b  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

Data fusion; Deep learnig; Optical remote sensing; Sentinel 1; Sentinel 2; Synthetic aperture radar (SAR)

Indexed keywords

DATA FUSION; GEOMETRICAL OPTICS; IMAGE FUSION; REMOTE SENSING; SPACE OPTICS; SYNTHETIC APERTURE RADAR;

ARTIFICIAL COLOR; DEEP LEARNIG; GENERATIVE MODEL; LOW LEVEL REPRESENTATION; OPTICAL REMOTE SENSING; REMOTE SENSING IMAGERY; SENTINEL-1; SENTINEL-2;

RADAR IMAGING;

EID: 85048356423     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5194/isprs-archives-XLII-2-1045-2018     Document Type: Conference Paper

References (12)

1. Bishop, C. M., 1994. Mixture density networks. Technical Report NCRG/94/004, Neural Computing Research Group, Aston University.
2. Deshpande, A., Lu, J., Yeh, M.-C., Chong, M. J. and Forsyth, D., 2017. Learning diverse image colorization. In: Proc. CVPR, Honolulu, HI, USA, pp. 6837-6845.
3. Harris, J. R. and Murray, R., 1990. IHS transform for the integration of radar imagery with other remotely sensed data. 56(12), pp. 1631-1641.
4. Kingma, D. and Ba, J., 2015. Adam: A method for stochastic optimization. In: Proc. ICLR, arXiv:1412.6980v9, San Diego, U.S.A.
5. Noboru, O. and Robertson, A. R., 2005. Standard and supplementary illuminants. In: Colorimetry, Wiley, pp. 92-96.
6. Pauli, H., 1976. Proposed extension of the CIE recommendation on "Uniform color spaces, color difference equations, and metric color terms". Journal of the Optical Society of America 66(8), pp. 866-867.
7. Pohl, C. and van Genderen, J. L., 1998. Multisensor image fusion in remote sensing: Concepts, methods and applications. International Journal of Remote Sensing 19(5), pp. 823-854.
8. Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C. and Fei-Fei, L., 2015. ImageNet large scale visual recognition challenge. International Journal of Computer Vision 115(3), pp. 211-252.
9. Schmitt, M. and Zhu, X., 2016. Data fusion and remote sensing - an ever-growing relationship. IEEE Geosci. Remote Sens. Mag. 4(4), pp. 6-23.
10. Schmitt, M., Tupin, F. and Zhu, X., 2017. Fusion of SAR and optical remote sensing data - challenges and recent trends. In: Proc. IGARSS, Fort Worth, TX, USA, pp. 5458-5461.
11. Tu, T.-M., Su, S.-C., Shyu, H.-C. and Huang, P. S., 2001. A new look at IHS-like image fusion methods. Information Fusion 2(3), pp. 177-186.
12. Zhang, R., Isola, P. and Efros, A., 2016. Colorful image col-orization. In: Proc. ECCV, Amsterdam, The Netherlands, p. 649-666.