A new approach for finding an appropriate combination of texture parameters for classification

Geocarto International

Volumn 25, Issue 4, 2010, Pages 295-313

  Pathak, Virendra ^a   Dikshit, Onkar ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Classification; Conjoint analysis; GLCM; Texture; Wavelet

Indexed keywords

ACCURACY ASSESSMENT; IMAGE ANALYSIS; IMAGE CLASSIFICATION; METHODOLOGY; MULTIVARIATE ANALYSIS; PARAMETERIZATION; QUANTITATIVE ANALYSIS; SPECTRAL RESOLUTION; TEXTURE; URBAN AREA; WAVELET ANALYSIS;

EID: 77953934618     PISSN: 10106049     EISSN: None     Source Type: Journal    
DOI: 10.1080/10106040903576195     Document Type: Article

References (28)

1. Aboufadel, E. and Schlicker, S., 1999. Discovering wavelets. New York: A Wiley-Interscience Publication, John Wiley & Sons, Inc.
2. Aguera, F., Aguilar, F.J., and Aguilar, M.A., 2008. Using texture analysis to improve perpixel classification of very high resolution images for mapping plastic greenhouses. ISPRS Journal of Photogrammetry & Remote Sensing, 63, 635-646.
3. Bian, L., 2003. Retrieving urban objects using a wavelet transform approach. Photogrammetric Engineering & Remote Sensing, 69 (2), 133-141.
4. Bouman, C. and Liu, B., 1991. Multiple resolution segmentation of textured images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13, 99-113.
5. Carroll, J.D. and Green, P.E., 1991. Psychometric method in marketing research: part 1, conjoint analysis. Journal of Market Research, 32, 113-120.
6. Chang, T. and Kuo, C.C.J., 1993. Texture analysis and classification with tree-structured wavelet transform. IEEE Transaction on Image Process, 2 (4), 429-441.
7. Chen, Z., Feng, T.J., and Houkes, Z., 1999. Texture segmentation based on wavelet and kohonen network for remotely sensed images. IEEE Transactions on Image Processing, 6, 816-821.
8. Chen, D., Stow, D.A., and Gong, P., 2004. Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case. International Journal of Remote Sensing, 25 (11), 2177-2192.
9. Chui, C.K., 1992. An introduction to wavelets. San Diego: Academic Press, Inc, Harcourt Brace Jovanovich publishers.
10. Congalton, R.G. and Green, K., 1999. Assessing the accuracy of remotely sensed data: principles and practices. USA: CRC Press, Inc.
11. Gong, P., Marceau, D.J., and Howarth, P.J., 1992. A comparison of spatial feature extraction algorithms for land-use classification with SPOT HRV data. Remote Sensing of Environment, 40, 137-151.
12. Gool, L.V., Dewaele, P., and Qosterlinck, A., 1985. Texture analysis, anno. 1983. Computer Vision Graphics and Image Processing, 29, 336-357.
13. Graps, A., 1995. An introduction to wavelets. IEEE Computer Science Engineering. 674-693, summer 1995.
14. Green, P.E. and Srinivasan, V., 1978. Conjoint analysis in consumer research: issue and outlook. Journal of Consumer Research, 5 (September), 103-123.
15. Green, P.E. and Srinivasan, V., 1990. Conjoint analysis in marketing: new developments with implications for research and practice. Journal of Marketing, 54 (4), 3-19.
16. Green, P.E. and Wind, Y., 1975. New way to measure consumers' judgements. Harvard Business Review, 53, 107-117.
17. Hair, J.F., et al., 1998. Multivariate data analysis. 5th ed. NJ, USA: Prentice-Hall International Inc.
18. Haralick, R.M., 1979. Statistical and structural approaches to texture. Proceeding of the IEEE, 67,786-804.
19. Haralick, R.M., Shanmugam, K., and Dinstein, I., 1973. Textural features for image classification. IEEE Transaction on Systems, Man and Cybernetics, SMC-3, 610-621.
20. Lu, D., Batisstella, M., and Moran, E., 2007. Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM{thorn} and Radarsat data. International Journal of Remote Sensing, 28 (24), 5447-5459.
21. Mallat, S.G., 1989. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11 (7), 674-693.
22. Marceau, D.J., et al., 1990. Evaluation of the gray-level co-occurrence matrix method for land cover classification using SPOT imagery. IEEE Transaction on Geosciences and Remote Sensing, 28, 513-519.
23. Misiti, M., et al., 2000. Wavelet toolbox user's guide. Natic, MA: The Math works, Inc.
24. Pathak, V. and Dikshit, O., 2006. Conjoint analysis for quantification of relative importance of various factors affecting BPANN classification of urban environment. International Journal of Remote Sensing, 27 (21), 4769-4789.
25. Unser, M. and Eden, M., 1989. Multiresolution feature extraction and selection for texture segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 717-728.
26. Yashon, O.O., Ngigi, T.G., and Tateishi, R., 2006. On the optimization and selection of wavelet texture for feature extraction from high-resolution satellite imagery with application towards urban-tree delineation. International Journal of Remote Sensing, 27 (1),73-104.
27. Young, R.K., 1993. Wavelet theory and its applications. Boston: Kluwer Academic Publishers.
28. Zhu, C. and Yang, X., 1998. Study of remote sensing image texture analysis and classification using wavelet. International Journal of Remote Sensing, 14 (3), 615-619.