Comparison and Fusion of Co-occurrence , Gabor and MRF Texture Features for Classification of SAR Sea-Ice Imagery

@inproceedings{Clausi2000ComparisonAF,
  title={Comparison and Fusion of Co-occurrence , Gabor and MRF Texture Features for Classification of SAR Sea-Ice Imagery},
  author={David A. Clausi},
  year={2000}
}
Image texture interpretation is an important aspect of the computer-assisted discrimination of Synthetic Aperture Radar (SAR) sea-ice imagery. Co-occurrence probabilities are the most common approach used to solve this problem. However, other texture feature extraction methods exist that have not been fully studied for their ability to interpret SAR sea-ice imagery. Gabor filters and Markov random fields (MRF) are two such methods considered here. Classification and significance level testing… CONTINUE READING
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