A technique has been suggested for multisensor data fusion to obtain landcover classification. It takes care of feature level fusion with Dempster-Shafer rule and data level fusion with Markov Random Field model based approach vis-a-vis for determining the optimal segmentation. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two illustrations of data fusion of optical images and a Synthetic Aperture Radar (SAR) image is presented and accuracy results are compared with those of some recent techniques in literature for the same image data. © Springer-Verlag 2004.
CITATION STYLE
Sarkar, A., Banerjee, N., Nair, P., Banerjce, A., Brahma, S., Kartikeyan, B., & Majumder, K. L. (2004). A MRF based segmentatiom approach to classification using dempster shafer fusion for multisensor imagery. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3212, 421–428. https://doi.org/10.1007/978-3-540-30126-4_52
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