Cloud removal from optical satellite imagery with SAR imagery using sparse representation

IEEE Geoscience and Remote Sensing Letters

Volumn 12, Issue 5, 2015, Pages 1046-1050

  Huang, Bo ^a   Li, Ying ^b   Han, Xiaoyu ^b   Cui, Yuanzheng ^a   Li, Wenbo ^b   Li, Rongrong ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Cloud removal; optical satellite imagery; sparserepresentation (SR); synthetic aperture radar (SAR) imagery

Indexed keywords

RADAR; RADIOMETERS; SATELLITES; SPACE-BASED RADAR; SYNTHETIC APERTURE RADAR;

CLOUD REMOVAL; HIGH-FREQUENCY INFORMATIONS; LOW AND HIGH FREQUENCIES; OPTICAL SATELLITE IMAGERY; OPTICAL SATELLITE IMAGES; SPARSE REPRESENTATION; SYNTHETIC APERTURE RADAR (SAR) IMAGES; SYNTHETIC APERTURE RADAR IMAGERY;

SATELLITE IMAGERY;

EID: 85027927647     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2377476     Document Type: Article

References (13)

1. C. Lin, P. Tsai, K. Lai, and J. Chen, quot;Cloud removal from multitemporal satellite images using information cloning, quot;IEEE Trans. Geosci. Remote Sens., vol. 51, no. 1, pp. 232-241, Jan. 2013.
2. A. Maalouf, P. Carre, B. Augereau, and C. Fernandez-Maloigne, quot;A bandelet-based inpainting technique for clouds removal from remotely sensed images,quot; IEEE Trans. Geosci. Remote Sens., vol. 47, no. 7, pp. 2363-2371, Jul. 2009.
3. L. Lorenzi, F. Melgani, and G. Mercier, quot;Inpainting strategies for reconstruction of missing data in VHR images,quot; IEEE Trans. Geosci. Remote Sens., vol. 8, no. 5, pp. 914-918, Sep. 2011.
4. Z. Wang, J. Jin, J. Liang, K. Yan, and Q. Peng, quot;A new cloud removal algorithm for multi-spectral images,quot; in Proc. SAR MIPPR, 2005, pp. 230-240.
5. P. Rakwatin, W. Takeuchi, and Y. Yasuoka, quot;Restoration of Aqua MODIS band 6 using histogram matching and local least squares fitting,quot; IEEE Trans. Geosci. Remote Sens., vol. 47, no. 2, pp. 613-627, Feb. 2009.
6. F. Melgani, quot;Contextual reconstruction of cloud-contaminated multitemporal multispectral images,quot; IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 442-455, Feb. 2006.
7. E. Robert, C. Berger, C. Thiel, and C. Schmullius, quot;Removal of optically thick clouds from multi-spectral satellite images using multi-frequency SAR data,quot; Remote Sens., vol. 5, pp. 2973-3006, Jun. 2013.
8. L. Alparone, S. Baronti, A. Garzelli, and F. Nencini, quot;Landsat ETM+ and SAR image fusion based on generalized intensity modulation,quot; IEEE Trans. Geosci. Remote Sens., vol. 42, no. 12, pp. 2832-2839, Dec. 2004.
9. M. Törmä, J. Lumme, N. Patrikainen, and K. Luojus, quot;Fusion of low resolution optical and high resolution SAR data for land cover classification,quot; in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2004, vol. 4, pp. 2680-2683.
10. N. Hoan and R. Tateishi, quot;Cloud removal of optical image using SAR data for ALOS application: Experimenting on simulated ALOS data,quot; in Proc. Int. Archives Photogramm., Remote Sens. Spatial Inf. Sci., Beijing, China 2008, vol. 37, pp. 379-384.
11. R. Rubinstein, A. M. Bruckstein, and M. Elad, quot;Dictionaries for sparse representation modeling,quot; Proc. IEEE, vol. 98, no. 6, pp. 1045-1057, Jun. 2010.
12. C. Huang et al., quot;Automated masking of cloud and cloud shadow for forest change analysis using Landsat images,quot; Int. J. Remote Sens., vol. 31, no. 20, pp. 5449-5464, Jun. 2010.
13. B. Huang and H. Song, quot;Spatiotemporal reflectance fusion via sparse representation,quot; IEEE Trans. Geosci. Remote Sens., vol. 50, no. 10, pp. 3707-3716, Oct. 2012.