A fast method to determine co-occurrence texture features

IEEE Transactions on Geoscience and Remote Sensing

Volumn 36, Issue 1, 1998, Pages 298-300

  Clausi, David A ^a   Jernigan, M ^b  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; IMAGE UNDERSTANDING; MATRIX ALGEBRA;

CO OCCURRENCE TEXTURE FEATURES; GREY LEVEL CO OCCURRENCE MATRICES (GLCM);

REMOTE SENSING;

EID: 0031647575     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.655338     Document Type: Article

References (7)

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3. M. E. Shokr, Evaluation of second-order texture parameters for sea ice classification from radar images J. Geophys. Res., vol. 96, no. C6, pp. 10625-10640, June 1991.
4. D. A. Clausi, Texture segmentation of SAR sea ice imagery Ph.D. dissertation, Univ. Waterloo, Waterloo, Ont., Canada, 1996.
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6. T. Hirose, T. Heacock, and R. Duncan, A report on the evaluation of ice classification algorithms Tech. Rep., prepared by Noetix Research Inc. for Environment Canada Ice Branch and Ice Applications Group-Canada Center for Remote Sensing, Oct. 1993.
7. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, 1st ed. Toronto, Ont., Canada: Wiley, 1973.