Texture Representation of SAR Sea Ice Imagery Using Multi-Displacement Co-Occurrence Matrices
Abstract-- In this paper, we desribe mdti-displacement cooccurrence matrices for re~enting W ice textures of SAR imagery. Our design of co-occcurrence matrices captures local relationships among neighboring pixels and global links among distant pixels, an advantage over other existing versions of co...
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| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.70.3856 http://www.ittc.ku.edu/publications/documents/Soh1996_igarss96-6.pdf |
| Summary: | Abstract-- In this paper, we desribe mdti-displacement cooccurrence matrices for re~enting W ice textures of SAR imagery. Our design of co-occcurrence matrices captures local relationships among neighboring pixels and global links among distant pixels, an advantage over other existing versions of co-occurrence matrices. As a result, it can adequately represent micro textures, such as grainy details, and macro textures, such as patchy blocks. We have conducted experiments to compare our multi-displacement co-occurrence matrices with other existing versions using Bayesian linear discrimination. We have found that our design is the most texturally representative in terms of classification accuraci = in both training and test datasets. In addition, we have applied this design to sea ice texture analysis which includes detection and localization, and subsequent image-texture mapping. |
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