An automated region growing algorithm for segmentation of texture regions in sar images

International Journal of Remote Sensing

Volumn 19, Issue 18, 1998, Pages 3595-3606

  Lira, J ^a   Frulla, L ^b  

^a UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

^b Facultad de Ciencias Naturales e Instituto M Lillo   (Argentina)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; GEOMORPHOLOGY; IMAGE ANALYSIS; IMAGE SEGMENTATION; RADAR IMAGING; SIGNAL FILTERING AND PREDICTION; SYNTHETIC APERTURE RADAR;

GEOMETRIC FILTER; SPECKLE REDUCTION;

REMOTE SENSING;

ALGORITHM; GEOMORPHOLOGY; IMAGE PROCESSING; SYNTHETIC APERTURE RADAR; TEXTURE;

EID: 0032450949     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311698213830     Document Type: Article

References (19)

1. Crimmins, T. R., 1985, Geometric Filter For Speckle Reduction. Applied Optics, 24, 1438-1443
2. Escalante-Ramirez, B., Lira, J., 1996, Performance-oriented analysis evaluation of modern adaptive speckle reduction techniques in SAR images. Proceedings, SPIE’s 40th Annual Meeting, San Diego, California, 2564 (Bellingham, WA: SPIE), pp. 98-110
3. Derin, H., Keuy, P. A., Vezina, G., Labitt, S. G., 1990, Modeling segmentation of speckled images using complex data. I.E.E.E. T ransactions on Geoscience Remote Sensing, 28, 76-86
4. Frost, V. S., Stiles, J., Shanmugan, K., Holtzmann, J., 1982, A model for radar images its application to adaptive digital filtering of multiplicative noise. I.E.E.E. Transactions on Pattern Analysis Machine Intelligence, PAMI-4, 157-166
5. Gong, P., Howarth, P. J., 1992, Frequency-based contextual classi ® cation gray-level vector reduction for land-use identification. Photogrammetric Engineering Remote Sensing, 58, 423-437
6. Gotlieb, C. C., Kreyszig, H. E., 1990, Texture descriptors based on co-occurrence matrices. Computer Vision, Graphics, Image Processing, 51, 70-86
7. Haralick, R. M., 1979, Statistical structural approaches to texture. Proceedings of the I.E.E.E, 67, 304-322
8. Kai, L., Muner, J. P., 1991, Segmenting satellite imagery: a region growing scheme. Proceedings, International Geoscience Remote Sensing Symposium, Helsinki University of Technology, Espoo, Finland, June (New York: IEEE) pp. 3- 6
9. Kuan, D. T., Sawchuk, A. A., Strand, T. C., Chavel, P., 1985, Adaptive noise smoothing filter for images with signal-dependent noise. I.E.E.E. T ransactions on Pattern Analysis Machine Intelligence, PAMI-7, 165-167
10. Lee, J. S., 1986, Speckle suppression analysis for synthetic aperture radar images. Optical Engineering, 25, 636-643
11. Lee, J. S., Jurkevich, I., Dewaele, P., Wambacq, P., Oosteninck, A., 1994, Speckle filtering of synthetic aperture radar images: a review. Remote Sensing Reviews, 8, 313-340
12. Li, Ch., 1988, Two adaptive filters for speckle reduction in SAR images by using the variance ratio. International Journal of Remote Sensing, 9, 641-653
13. Morel, J. M., Solimini, S., 1995, Variational Methods in Image Segmentation (Woodbine, NJ: Birkhauser)
14. Nguyen, H. H., Cohen, P., 1993, Gibbs random fields, fuzzy clustering, the unsupervised segmentation of textured images. CVGIP: Graphical Models Image Processing, 55, 1-19
15. Olsen, E. R., Ramsey, R. D., Winn, D. S., 1993, A modified fractal dimension as a measure of landscape diversity. Photogrammetric Engineering Remote Sensing, 59, 1517-1520
16. Pastrana, R., 1996, Restoration of Digital Images: Elimination of Noise by Means of a Geometric Filter, BSc thesis, School of Electronic Sciences, Autonomous University of Puebla, Mexico
17. Pratt, W. K., 1991, Digital Image Processing (New York: Wiley Interscience)
18. Raafat, H. M., Wong, A. K. C., 1988, A texture information-directed region growing algorithm for image segmentation region classification. Computer Vision, Graphics, Image Processing, 43, 1-21
19. Zucker, T. R., Dubuf, J. M. H., 1993, A review of recent texture segmentation feature extraction techniques. CVGIP: Image Understanding, 57, 359-372