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Sonar image segmentation using an unsupervised hierarchical MRF model
2000
IEEE Transactions on Image Processing
This paper is concerned with hierarchical Markov random field (MRF) models and their application to sonar image segmentation. We present an original hierarchical segmentation procedure devoted to images given by a high-resolution sonar. The sonar image is segmented into two kinds of regions: shadow (corresponding to a lack of acoustic reverberation behind each object lying on the sea-bed) and sea-bottom reverberation. The proposed unsupervised scheme takes into account the variety of the laws
doi:10.1109/83.847834
pmid:18262959
fatcat:kz3ma6lv2rfedc25qduu2zcnpi