A comprehensive, automated approach to determining sea ice thickness from SAR data

Documents an approach to sea ice classification through a combination of methods, both algorithmic and heuristic. The resulting system is a comprehensive technique, which uses dynamic local thresholding as a classification basis and then supplements that initial classification using heuristic geophysical knowledge organized in expert systems. The dynamic local thresholding method allows separation of the ice into thickness classes based on local intensity distributions. Because it utilizes the data within each image, it can adapt to varying ice thickness intensities to regional and seasonal changes and is not subject to limitations caused by using predefined parameters. >

[1]  Takashi Matsuyama Knowledge-Based Aerial Image Understanding Systems and Expert Systems for Image Processing , 1987, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Ron Kwok,et al.  Ice Classification Algorithm Development and Verification for the Alaska Sar Facility Using Aircraft Imagery , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

[3]  C. Chow,et al.  Automatic boundary detection of the left ventricle from cineangiograms. , 1972, Computers and biomedical research, an international journal.

[4]  Michihiro Mese,et al.  A process for detecting defects in complicated patterns , 1973, Comput. Graph. Image Process..

[5]  A. Rosenfeld,et al.  A Note on the Use of Second-Order Gray Level Statistics for Threshold Selection. , 1977 .

[6]  Leen-Kiat Soh,et al.  A feature extraction technique for synthetic aperture radar (SAR) sea ice imagery , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[7]  E. Alparslan,et al.  Image enhancement by local histogram stretching , 1981 .

[8]  Shmuel Peleg Iterative histogram modification. II , 1977 .

[9]  Tardi Tjahjadi,et al.  A knowledge based system for image understanding , 1989 .

[10]  J. G. McAvoy,et al.  A Knowledge Based System for the Interpretation of Sar Images of Sea Ice , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

[11]  Martin D. Levine,et al.  Rule-based image segmentation: A dynamic control strategy approach , 1985, Comput. Vis. Graph. Image Process..

[12]  Ching Y. Suen,et al.  A fast parallel algorithm for thinning digital patterns , 1984, CACM.

[13]  Rangasami L. Kashyap,et al.  Estimation of probability density and distribution functions , 1968, IEEE Trans. Inf. Theory.

[14]  Tzay Y. Young,et al.  Stochastic estimation of a mixture of normal density functions using an information criterion , 1970, IEEE Trans. Inf. Theory.

[15]  Azriel Rosenfeld,et al.  Histogram modification for threshold selection , 1977 .

[16]  Stephen Wharton,et al.  A Spectral-Knowledge-Based Approach for Urban Land-Cover Discrmination , 1987, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Sivaprasad Gogineni,et al.  The combination of algorithmic and heuristic methods for the classification of sea ice imagery , 1994 .