Improved texture recognition of SAR sea ice imagery by data fusion of MRF features with traditional methods

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 3, Issue , 2001, Pages 1170-1172

  Clausi, David A ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER APPLICATIONS; MARKOV PROCESSES; OBJECT RECOGNITION; PROBABILITY; PROBLEM SOLVING; SYNTHETIC APERTURE RADAR;

DATA FUSION; GABOR FILTER; GREY LEVEL OCCURRENCE PROBABILITY; MARKOV RANDOM FIELD; SEA ICE IMAGERY; TEXTURE RECOGNITION;

REMOTE SENSING;

EID: 0035573540     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. SAR sea ice discrimination using texture statistics: A multivariate approach
2. Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices
3. Textural features for image classification
4. Comparison and fusion of co-occurrence, Gabor, and MRF texture features for classification of SAR sea ice imagery
5. Unsupervised texture segmentation using Gabor filters
6. Multichannel texture analysis using localized spatial filters
7. Designing Gabor filters for optimal texture separability
8. Classification of textures using Gaussian Markov random fields
9. On the statistical analysis of dirty pictures
10. Unsupervised texture segmentation using Markov random field models
11. On the estimation of spring melt in the North Water (NOW) using RADARSAT-1