Gabor vs. GMRF features for SAR imagery classification Export

@inproceedings{citeulike:944798, abstract = {A comparison of the ability to discriminate among distinct regions in synthetic aperture radar (SAR) imagery using textural features based on two different methods is presented. Features are generated from Gauss Markov random field (GMRF) model parameters and from Gabor convolution energies. The discrimination ability is evaluated in terms of misclassification errors resulting from tests performed on a patchwork of different MSTAR clutter regions}, author = {Torres-Torriti, M. and Jouan, A.}, citeulike-article-id = {944798}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958305}, journal = {Image Processing, 2001. Proceedings. 2001 International Conference on}, keywords = {classification, fields, gabor, gmrf, markov, random, sar}, pages = {1043--1046 vol.3}, posted-at = {2006-11-15 15:47:19}, priority = {5}, title = {Gabor vs. GMRF features for SAR imagery classification}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958305}, volume = {3}, year = {2001} }

TY - CONF ID - citeulike:944798 L3 - citeulike-article-id:944798 N2 - A comparison of the ability to discriminate among distinct regions in synthetic aperture radar (SAR) imagery using textural features based on two different methods is presented. Features are generated from Gauss Markov random field (GMRF) model parameters and from Gabor convolution energies. The discrimination ability is evaluated in terms of misclassification errors resulting from tests performed on a patchwork of different MSTAR clutter regions JF - Image Processing, 2001. Proceedings. 2001 International Conference on EP - 1046 vol.3 TI - Gabor vs. GMRF features for SAR imagery classification VL - 3 SP - 1043 KW - classification KW - fields KW - gabor KW - gmrf KW - markov KW - random KW - sar AU - Torres-Torriti, M AU - Jouan, A PY - 2001/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958305 ER -