A robust built-up area presence index by anisotropic rotation-invariant textural measure

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

Volumn 1, Issue 3, 2008, Pages 180-192

  Pesaresi, Martino ^a   Gerhardinger, Andrea ^a   Kayitakire, François ^a  

^a JOINT RESEARCH CENTRE   (Italy)

Author keywords

Automatic recognition; Built up areas; Human settlements; Textural analysis; Urban areas

Indexed keywords

NEURAL NETWORKS;

AUTOMATIC RECOGNITION; BUILT-UP AREAS; HUMAN SETTLEMENTS; TEXTURAL ANALYSIS; URBAN AREAS;

ANISOTROPY;

FUZZY MATHEMATICS; HUMAN SETTLEMENT; PANCHROMATIC IMAGE; RECOGNITION; SATELLITE DATA; TEXTURE; URBAN AREA; WAVELET ANALYSIS;

EID: 70350182935     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2008.2002869     Document Type: Article

References (26)

1. R. M. Haralick, K. Shanmugam, and I. Dinstein, "Texture features for image classification," IEEE Trans. Syst., Man, Cybern., vol. SMC-3, no. 11, pp. 610-621, Nov. 1973.
2. R. M. Haralick, "Statistical and structural approaches to texture" Proc. IEEE, vol. 67, no, 5, pp. 786-804, May 1979.
3. M. Pesaresi, "An optimized procedure to built space automatic recognition via Spot HRV panchromatic satellite data processing, in proceedings of ISTAT-EUROSTAT seminar," in Proc. The Impact-of Remote Sensing on the European Statistical Information System, Rome, Italy, Nov, 1995, pp.27-29.
4. P. Gong and P. J. Howarth, "The use of structural information for improving land-cover classification accuracies at the rural-urban fringe," Photogramm. Eng. Remote Sens., vol. 56, pp. 67-73, 1990.
5. P. Gong and P. J. Howarth, "Frequency-based contextual classification and grey-level vector reduction for land-use identification," Photogramm. Eng. Remote Sens., vol. 58, pp. 423-437, 1992.
6. A. Puissant, J. Hirsch, and C. Weber, "The utility of texture analysis to improve per-pixel classifications for high to very high spatial resolution imagery," Int. J. Remote Sens., vol. 26, no. 4, pp. 733-745, 2005.
7. Q. Zhang, J. Wang, P. Gong, and P. Shi, "Urban spatial pattern analysis from SPOT panchromatic imagery using textural analysis," Int. J. Remote Sens., vol. 24, no. 21, pp. 4137-4160, 2003.
8. M. Pesaresi, "Morphology and texture for the settlement structural description," presented at the ESF-GISDATA Specialist Meet. Remote Sensing and Urban Change, Strasbourg, Jun. 7-11, 1995.
9. M. Pesaresi and A. Bianchin, "Recognizig settlement structure using mathematical morphology and image texture measures," in Remote Sensing and Urban Analysis, J. P. Donnay and M. Barnsley, Eds. Londra, UX: Taylor & Francis, 1996.
10. M. Pesaresi and I. Kannellopoulos, "Discrimination of urban areas using textural and morphological features extracted from very high-resolution IRS-IC imagery," presented at the Int. Conf. Spatial Analysis and Environmental. Processes, Lisbon, Portugal, 1998.
11. M. Pesaresi and A. Bianchin, "Procedure to extract built area," presented at the ITC Int. Symp. Operationilization of Remote Sensing, Enschede, The Netherlands, Apr. 19-23, 1993.
12. M. Pesaresi, "A mixed morphological and spectral procedure to improve the accuracy of the built area classification from multisensor satellite data," presented at the ISMM Mathematical Morphology and its Applications to Signal Processing II, Fontainebleau, France; Sep. 7-9, 1994.
13. M. Pesaresi, "Texture analysis for urban pattern recognition using fine-resolution panchromatic satellite imagery," Geograph. Environ. Model., vol. 4, no. 1, pp. 47-67, 2000.
14. F. Lafarge, X. Descombes, and J. Zerubid, "Textural kernel for svm classification in remote sensing: Application to forest'fire detection and urban area extraction," in Proc. IEEE Int. Conf Image Processing 2005, vol. 3, pp. III-1096-III-1099.
15. M. De Martino, G. Macchiavello, and S. B. Serpico, "Partially supervised classification of optical high spatial resolution images in urban environment using spectral and textural information," in Proc. IEEE Int. Geoscience and Remote Sensing Symp., 2004, vol. 1, pp. 4896-4897.
16. J. Plaza, A. Plaza, P. Gamba, and G. Trianni, "Efficient multi-band texture analysis for remotely sensed data interpretation in urban areas," presented at the Urban Remote Sensing Joint Event, Paris, France, Apr. 11-13, 2007.
17. L. Peijun, H. Hongtao, and G. Jiancong, "Segmentation of high-resolution multispectral image based on extended morphological profiles," in Proc. IEEE Int. Geoscience and Remote Sensing Symp. 2007, pp. 1481-1484.
18. P. Zhong and R. Wang, "A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pt. 1, pp. 3978-3988, Dec. 2007.
19. L. Zadeh, Fuzzy Sets, Inf. Control, vol. 8, pp. 338-353, 1965.
20. J. Yaochu, Advanced Fuzzy Systems Design and Applications, 1st ed. Heidelberg, Germany: Physica-Verlag, Jan. 2003.
21. M. Pesaresi, "Textural classification of very high-resolution satellite imagery. empirical estimation of the interaction between window size and detection accuracy in urban environment," in Proc. Int. Conf. Image Processing, Kobe, Japan, Oct. 24-28,1999, vol. 1, pp. 114-118, 25AP3.3.
22. D. Chen, D. A., Stow, and P. Gong, "Examining the effect of spatial resolution and texture window size on classification accuracy: An urban environmgnt case," Int. J. Remote Sens., vol. 25, no. 11, pp. 2177-21, 2004.
23. B. W. Silverman, "Using Kernel density estimates to investigate multimodality," J. Roy. Statist. Soc. B, vol. 43, no. 1, pp. 97-99, 1981.
24. M. C. Jones, J. S. Marron, and S. J. Sheather, "A brief survey of bandwidth selection for density estimation," J. Amer. Statist. Assoc., vol. 91, no. 433, pp. 401-407, 1996.
25. J. Cohen, "Weighted kappa," Psych. Bull., vol. 70, pp. 71-94, 1968.
26. J. A. Richards, Remote Sensing Digital Image Analysis. An Introduction, 2nd ed. Berlin, Germany: Springer-Verlag, 1993.