| Title | Filament preserving segmentation for SAR sea ice imagery using a new statistical model |
| Publication Type | Conference Paper |
| Year of Publication | 2006 |
| Authors | Yu, Q., and D. A. Clausi |
| Conference Name | 18th International Conference on Pattern Recognition (ICPR) |
| Date Published | 08/2006 |
| Conference Location | Hong Kong |
| Keywords | Feature Extraction, filament preserving segmentation, geophysical signal processing, Image Denoising, image segmentation, Markov processes, Markov random field, narrow elongated features, noisy image segmentation, oceanographic techniques, radar imaging, SAR sea ice imagery, sea ice, ship navigation, spatial context constraints, statistical analysis, statistical model, synthetic aperture radar |
| Abstract | Modelling spatial context constraints using Markov random field (MRF) has been widely used in the segmentation of noisy images. Its applicability to SAR sea ice segmentation has also been demonstrated by Deng and Clausi (2005). However, most existing MRF models are not capable of preserving filaments, specifically leads and ridges for SAR sea ice, which are valuable for ship navigation applications and helpful for identifying certain ice types. A new statistical context model is proposed that can preserve such narrow elongated features while producing similar smooth segmentation results as those of existing MRF based approaches |
| DOI | 10.1109/ICPR.2006.561 |
