Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

baltsavias, emmanuel p.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: TECHNICAL SESSION 3 OBJECT AND IMAGE CLASSIFICATION

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: SCALE CHARACTERISTICS OF LOCAL AUTOCOVARIANCES FOR TEXTURE SEGMENTATION. Annett Faber, Wolfgang Förstner

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing,Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 67 Figure 9: Results of edge extraction: Upper row) aerial im age, lower row left) using intensity alone (s — 2.0, t = 2.0J, right) using the Laplacian box ( s x = 0.7, h = 2.0, m = 3, S2 = 4.0, t2 = 3.0,). REFERENCES A. C. Bovik, M. C. and Geisler, W. S., 1990. Multichannel texture analysis using localized spatial filters. IEEE Trans action on PAMI 12, pp. 55-73. Andrey, P. and Tarroux, P, 1996. Unsupervised texture segmentation using selectionist relaxation. Proc. of ECCV, pp. 483-491. Ballard, D. H. and Rao, R. P. N., 1994. Seeing behind oc clusions. In: Lecture Notes in Computer Scienes, Vol. 800, Springer Verlag, Heidelberg, pp. 274-285. Bigün, J. and du Buf, J. M. H., 1992. Geometric image primitives by complex moments in Gabor space and the ap plication to texture segmentation. In: Proceedings of Con ference on Computer Vision and Pattern Recognition, IEEE Computer Society Press, pp. 648-649. Burt, P. J. and Adelson, E. H., 1983. The Laplacian pyramid as a compact image code. IEEE Transactions on Commu nications COM-31 (4), pp. 532-540. Carlucci, L. A., 1976. A formal system for texture lan- gagues. Pattern Recognition 4(1), pp. 53-72. de Beuaville, J.-R, Bi, D. and Langlais, L., 1994. Texture segmentation using grey level rank-vectors. Graphics and Vision 3(4), pp. 667-674. Derin, H. and Cole, W. S., 1986. Segmentation of tex tured images using Gibbs random fields. Computer Vision, Graphics, and Image Processing 35 (1), pp. 72-98. Förstner, W., 1991. Statistische Verfahren für die automa tische Bildanalyse und ihre Bewertung bei der Objekterken nung und -Vermessung. München. DGK bei der Bay erischen Akademie der Wissenschaften, Reihe C, Heft 370. Fuchs, C., 1998. Extraktion polymorpher Bildstrukturen und ihre topologische und geometrische Gruppierung. München. DGK bei der Bayerischen Akademie der Wis senschaften, Reihe C, Heft 502. Figure 10: Results of edge extraction: Upper row) image ’’toys”, lower row left) using intensity alone (s — 2.0, t = 2.0), right) using level the Laplacian box ( si = 0.7, t } = 2.0, tii = 2, S2 — 2.0, ¿2 = “2.0). Haralick, R., 1979. Statistical and structural approaches to texture. In: Proceedings of IEEE, Vol. 67, No. 5, pp. 786- 804. Haralick, R. M. and Shapiro, L. G., 1992. Computer and Robot Vision, Volume I/ll. 1st edition, Addison-Wesley Pub lishing Company. Jahne, B., 1989. Digitale Bildverarbeitung. Springer. Julez, B. and Bergen, J. R., 1983. Textons, the fundamental elements in preattentive vision and perception of textures. Bell SystemTechnology Journal 62(6), pp. 1619-1645. Malik, J. and Perona, R, 1990. Preattentive texture dis crimination with early vision mechanism. Journal of Optical Society of America, pp. 923-932. Papoulis, A., 1984. Probability, Random Variables, and Stochastic Processes. Electrical Engineering, 2nd edition, McGraw-Hill. Reed, T. R. and du Buf, J. M. H., 1993. A review of recent texture segmentation and feature extraction tech niques. CVGIP: Image Understanding 57(3), pp. 359-372. Shao, J. and Forstner, W., 1994. Gabor wavelets for texture edge extraction. In: Proceedings of Symposium on Spatial Information from Digital Photogrammetry and Computer Vi sion, ISPRS Commission III, Munich, pp. 745-751. Weidner, U., 1994. Information preserving surface restora tion and feature extraction for digital elevation models. In: Proceedings of Symposium on Spatial Information from Digital Photogrammetry and Computer Vision, ISPRS Comm. Ill, Munich, pp. 908-915.

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