Contextual spatiospectral postreconstruction of cloud-contaminated images

IEEE Geoscience and Remote Sensing Letters

Volumn 5, Issue 2, 2008, Pages 204-208

  Benabdelkader, Souad ^a   Melgani, Farid ^b  

^a UNIVERSITY OF BATNA   (Algeria)

^b UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CONTAMINATED AREAS; END-USERS; ERROR MAPS; GENERAL METHODS; LANDSAT-7 ETM+; MULTI TEMPORALS; MULTI-SPECTRAL IMAGES; PREDICTION PROCESS; RE-CONSTRUCTION PROCESS; RECONSTRUCTED IMAGES; SPECTRAL CORRELATIONS;

REMOTE SENSING;

RESTORATION;

EID: 64149106236     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2008.915596     Document Type: Article

References (13)

1. G. Demoment, "Image reconstruction and restoration: Overview of common estimation structures and problems," IEEE Trans. Acoust., Speech, Signal Process., vol. 37, no. 12, pp. 2024-2036, Dec. 1989.
2. S. G. Narasimhan and S. K. Nayar, "Contrast restoration of weather degraded images," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 6, pp. 713-724, Jun. 2003.
3. D. G. Long, Q. Remund, and D. Daum, "A cloud-removal algorithm for SSM/I data," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 1, pp. 54-62, Jan. 1999.
4. B. Gao, P. Yang,W. Han, R. Li, andW. J.Wiscombe, "An algorithm using visible and 1.38-μm channels to retrieve cirrus cloud reflectances from aircraft and satellite data," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 8, pp. 1659-1668, Aug. 2002.
5. E. H. Helmer and B. Ruefenacht, "Cloud-free satellite image mosaics with regression trees and histogram matching," Photogramm. Eng. Remote Sens., vol. 71, no. 9, pp. 1079-1089, Sep. 2005.
6. E. G.Moody, M. D. King, S. Platnick, C. B. Schaaf, and F. Gao, "Spatially complete global spectral surface albedos: Value-added datasets derived from Terra MODIS land products," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 1, pp. 144-158, Jan. 2005.
7. F. Melgani, "Contextual reconstruction of cloud-contaminated multitemporal multispectral images," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 442-455, Feb. 2006.
8. F.Melgani and S. B. Serpico, "AMarkov random field approach to spatiotemporal contextual image classification," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 11, pp. 2478-2487, Nov. 2003.
9. F. Melgani and Y. Bazi, "Markovian fusion approach to robust unsupervised change detection in remotely sensed imagery," IEEE Geosci. Remote Sens. Lett., vol. 3, no. 4, pp. 457-461, Oct. 2006.
10. G. R. Cross and A. K. Jain, "Markov random field texture models," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-5, no. 1, pp. 25-39, Jan. 1983.
11. M. Shroder, H. Rehrauer, K. Seidel, and M. Datcu, "Spatial information retrieval from remote-sensing images-Part II: Gibbs-Markov random fields," IEEE Trans. Geosci. Remote Sens., vol. 36, no. 5, pp. 1446-1455, Sep. 1998.
12. L. Yin, R. Yang, M. Gabbouj, and Y. Neuvo, "Weighted median filters: A tutorial," IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 43, no. 3, pp. 157-192, Mar. 1996.
13. A. Smola and B. Schölkopf, "A tutorial on support vector regression," Roy. Holloway College, Univ. London, London, U.K., NeuroCOLT Tech. Rep. NC-TR-98-030, 1998.