Bag-of-Words and Object-Based Classification for Cloud Extraction from Satellite Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 8, Issue 8, 2015, Pages 4197-4205

  Yuan, Yi ^a   Hu, Xiangyun ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Bag of words (BOW); cloud detection; satellite images; scale invariant feature transform (SIFT); support vector machines (SVMs); visual words

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); EXTRACTION; FEATURE EXTRACTION; IMAGE RETRIEVAL; INFORMATION RETRIEVAL; PIXELS; REMOTE SENSING; SATELLITES; SUPPORT VECTOR MACHINES; VECTORS;

BAG OF WORDS; CLOUD DETECTION; SATELLITE IMAGES; SCALE INVARIANT FEATURE TRANSFORMS; SUPPORT VECTOR MACHINE (SVMS); VISUAL WORD;

SATELLITE IMAGERY;

ALGORITHM; DETECTION METHOD; IMAGE ANALYSIS; IMAGE CLASSIFICATION; PIXEL; PRECISION; REMOTE SENSING; SATELLITE IMAGERY; TRANSFORM;

EID: 84941906787     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2015.2431676     Document Type: Article

References (31)

1. R. W. Saunders, "An automated scheme for the removal of cloud contamination from AVHRR radiances over western Europe," Int. J. Remote Sens., vol. 7, no. 7, pp. 867-886, 1986.
2. R. W. Saunders and K. T. Kriebel, "An improved method for detecting clear sky and cloudy radiances from AVHRR data," Int. J. Remote Sens., vol. 9, no. 1, pp. 123-150, 1988.
3. K. T. Kriebel et al., "The cloud analysis tool APOLLO: improvements and validations," Int. J. Remote Sens., vol. 24, no. 12, pp. 2389-2408, 2003.
4. R. R. Irish et al., "Characterization of the Landsat-7 ETM+ automated cloud-cover assessment (ACCA) algorithm," Photogramm. Eng. Remote Sens., vol. 72, no. 10, pp. 1179-1188, 2006.
5. Q. Zhang and C. Xiao, "Cloud detection of RGB color aerial photographs by progressive refinement scheme," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 11, pp. 7264-7275, Nov. 2014.
6. C. I. Christodoulou, S. C. Michaelides, and C. S. Pattichis, "Multifeature texture analysis for the classification of clouds in satellite imagery," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 11, pp. 2662-2668, 2003.
7. H. K. Chethan, R. Raghavendra, and G. H. Kumar, "Texture based approach for cloud classification using SVM," in Proc. Int. Conf. Adv. Recent Technol. Commun. Comput. (ARTCom'09), Kottayam, Kerala, 2009, pp. 688-690.
8. S. Le Hégarat-Mascle and C. André, "Use of Markov random fields for automatic cloud/shadow detection on high resolution optical images," ISPRS J. Photogramm. Remote Sens., vol. 64, no. 4, pp. 351-366, 2009.
9. Z. Zhu and C. E. Woodcock, "Object-based cloud and cloud shadow detection in Landsat imagery," Remote Sens. Environ., vol. 118, pp. 83-94, Mar. 2012.
10. S. Jin et al., "Automated cloud and shadow detection and filling using two-date Landsat imagery in the USA," Int. J. Remote Sens., vol. 34, no. 5, pp. 1540-1560, Mar. 2013.
11. N. R. Goodwin, L. J. Collett, R. J. Denham, N. Flood, and D. Tindall, "Cloud and cloud shadow screening across Queensland, Australia: An automated method for Landsat TM/ETM+ time series," Remote Sens. Environ., vol. 134, pp. 50-65, Jul. 2013.
12. Z. Zhu and C. E. Woodcock, "Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change," Remote Sens. Environ., vol.152, pp. 217-234, Sep. 2014.
13. A. Fisher, "Cloud and cloud-shadow detection in SPOT5 HRG imagery with automated morphological feature extraction," Remote Sens., vol. 6, no. 1, pp. 776-800, 2014.
14. G. Csurka et al., "Visual categorization with bags of keypoints," in Proc. Workshop Stat. Learn. Comput. Vis. (ECCV), 2004, vol. 1, pp. 1-22.
15. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
16. V. Vapnik, The Nature of Statistical Learning Theory. New York, NY, USA: Springer, 2000.
17. C. Rother, V. Kolmogorov, and A. Blake, "Grabcut: Interactive foreground extraction using iterated graph cuts, ACM Trans. Graphics (TOG), vol. 23, no. 3, pp. 309-314, 2004.
18. R. Achanta et al., "SLIC superpixels compared to state-of-the-art superpixel methods," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 11, pp. 2274-2282, 2012.
19. D. D. Lewis, "Naive (Bayes) at forty: The independence assumption in information retrieval," in Machine Learning: ECML-98. New York, NY, USA: Springer, 1998, pp. 4-15.
20. L. Fei-Fei and P. Perona, "A bayesian hierarchical model for learning natural scene categories," Comput. Vis. Pattern Recog., 2005, vol. 2, pp. 524-531.
21. J. Yang et al. "Evaluating bag-of-visual-words representations in scene classification," in Proc. Int. Workshop Multimedia Inf. Retrieval, 2007, pp. 197-206.
22. N. H. Dardas and N. D. Georganas, "Real-time hand gesture detection and recognition using bag-of-features and support vector machine techniques," Instrum. Meas., vol. 60, no. 11, pp. 3592-3607, 2011.
23. J. Sivic and A. Zisserman, "Video Google: A text retrieval approach to object matching in videos," in Proc. IEEE Int. Conf. Comput. Vis., 2003, pp. 1470-1477.
24. H. Jégou, M. Douze, and C. Schmid, "Packing bag-of-features," in Proc. Int. Conf. Comput. Vis., 2009, pp. 2357-2364.
25. C.-C. Chang and C.-J. Lin, "LIBSVM: a library for support vector machines," ACM Trans. Intell. Syst. Technol. (TIST), vol. 2, no. 3, pp. 27, 2011.
26. C. M. Bishop, Pattern Recognition and Machine Learning. New York, NY, USA: Springer, 2006.
27. N. Otsu, "A threshold selection method from gray-level histograms," Automatica, vol. 11, no. 285-296, pp. 23-27, 1975.
28. (2014). RapidEye [Online]. Available: http://eyefind.rapideye.com/ [29] (2014).
29. Landsat [Online]. Available: http://landsatlook.usgs.gov/
30. H. Bay, T. Tuytelaars, and L. V. Gool, "Surf: Speeded up robust features," in Computer Vision-ECCV. New York, NY, USA: Springer, 2006, pp. 404-417.
31. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," Comput. Vis. Pattern Recog., vol. 1, pp. 886-893, 2005.