@article {222,
	title = {Icesynth II: Synthesis of SAR sea-ice imagery using region-based posterior sampling},
	journal = {IEEE Geosciences and Remote Sensing Letters},
	volume = {7},
	year = {2010},
	pages = {348 - 351},
	abstract = {<p>A novel method for synthesizing synthetic aperture radar (SAR) sea-ice imagery named IceSynth II is presented. A Markov random field model is assumed, and a conditional sampling approach is used to learn local conditional posterior probability distributions on a regional basis. Synthetic SAR sea-ice images and the associated ground-truth segmentations are generated using a region-based posterior sampling approach. Experimental results using single-polarization RADARSAT-1 and dual-polarization RADARSAT-2 SAR sea-ice imagery provided by the Canadian Ice Service show that IceSynth II is capable of producing SAR sea-ice imagery that is more realistic than existing approaches. The synthesized images are well suited for performing systematic and reliable objective evaluation of SAR sea-ice image segmentation methods.</p>
},
	keywords = {Conditional, Markov random field (MRF), multivariate region growing, posterior, sampling ice, synthesis, synthetic aperture radar (SAR)},
	author = {A Wong and P Yu and W Zhang and D A. Clausi}
}
