Texture Representation of SAR Sea Ice Imagery Using Multi-Displacement Co-Occurrence Matrices

• Main Author: Costaa Tsatsoulis
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: Sea ice
• 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

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.