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Volumn 38, Issue , 2010, Pages 690-696

Development of a supervised software tool for automated determination of optimal segmentation parameters for ecognition

Author keywords

Abstraction; Advancement; Classification; High resolution; Image; Land cover; Software

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER SOFTWARE; FUZZY LOGIC; REMOTE SENSING;

EID: 84924079964     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (28)

References (11)
  • 1
    • 0001812168 scopus 로고    scopus 로고
    • Multiresolution segmentation - An optimization approach for high quality multi-scale image segmentation
    • Ed. J. Strobl et al. AGIT Symposium, Salzburg, Germany, 2000
    • Baatz, M. and A. Schäpe, 2000, Multiresolution Segmentation - An Optimization Approach for High Quality Multi-Scale Image Segmentation. Angewandte Geographische Informationsverarbeitung XII, Ed. J. Strobl et al. AGIT Symposium, Salzburg, Germany, 2000. pp. 12-23.
    • (2000) Angewandte Geographische Informationsverarbeitung XII , pp. 12-23
    • Baatz, M.1    Schäpe, A.2
  • 4
    • 0142242343 scopus 로고    scopus 로고
    • Preliminary evaluation of ecognition object-based software for cut block delinieation and feature extraction
    • Flanders, D., M.Hall-Beyer, and J. Pereverzoff, 2003. Preliminary Evaluation of eCognition Object-Based software for Cut Block Delinieation and Feature Extraction. Canadian Journal of Remote Sensing, Vol. 29, No. 4, pp. 441-452.
    • (2003) Canadian Journal of Remote Sensing , vol.29 , Issue.4 , pp. 441-452
    • Flanders, D.1    Hall-Beyer, M.2    Pereverzoff, J.3
  • 7
    • 57049134363 scopus 로고    scopus 로고
    • Performance assessment of automatic feature extraction tools on high resolution imagery
    • November 6-10, 2006, San Antonio, Texas
    • Lavigne, D.A., G. Hong and Y. Zhang, 2006. Performance Assessment of Automatic Feature Extraction Tools on High Resolution Imagery, MAPPS/ASPRS 2006 Fall Conference, November 6-10, 2006, San Antonio, Texas.
    • (2006) MAPPS/ASPRS 2006 Fall Conference
    • Lavigne, D.A.1    Hong, G.2    Zhang, Y.3
  • 8
    • 70349231059 scopus 로고    scopus 로고
    • An efficient multiscale srmmhr (statistical region merging and minimum heterogeneity rule) segmentation method for high-resolution remote sensing imagery
    • Li, H., Gu, H., Han, Y. and Yang, J., 2009. An efficient multiscale SRMMHR (Statistical Region Merging and Minimum Heterogeneity Rule) segmentation method for high-resolution remote sensing imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2(2), pp. 67-73.
    • (2009) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol.2 , Issue.2 , pp. 67-73
    • Li, H.1    Gu, H.2    Han, Y.3    Yang, J.4
  • 9
    • 84868034722 scopus 로고    scopus 로고
    • Object-oriented classification: Classification of pan-sharpened quickbird imagery and a fuzzy approach to improving image segmentation efficiency
    • M.Sc.E. thesis, University of New Brunswick, Fredericton, New Brunswick
    • Maxwell, T., 2005. Object-Oriented Classification: Classification of Pan-Sharpened QuickBird Imagery and a Fuzzy Approach to Improving Image Segmentation Efficiency. M.Sc.E. thesis, Department of Geodesy and Geomatics Engineering Technical report No. 233, University of New Brunswick, Fredericton, New Brunswick, 157 pp.
    • (2005) Department of Geodesy and Geomatics Engineering Technical Report No. 233
    • Maxwell, T.1
  • 10
    • 77649086964 scopus 로고    scopus 로고
    • Real world objects in GEOBIA through the exploitation of existing digital cartography and image segmentation
    • Smith, G.M., and R.D. Morton, 2010. Real World Objects in GEOBIA through the Exploitation of Existing Digital Cartography and Image Segmentation, Photogrammetric Engineering & Remote Sensing, Vol. 76, No. 2,, pp. 163- 171.
    • (2010) Photogrammetric Engineering & Remote Sensing , vol.76 , Issue.2 , pp. 163-171
    • Smith, G.M.1    Morton, R.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.