|Title||Icesynth II: Synthesis of SAR sea-ice imagery using region-based posterior sampling|
|Publication Type||Journal Article|
|Year of Publication||2010|
|Authors||Wong, A., P. Yu, W. Zhang, and D. A. Clausi|
|Journal||IEEE Geosciences and Remote Sensing Letters|
|Pagination||348 - 351|
|Keywords||Conditional, Markov random field (MRF), multivariate region growing, posterior, sampling ice, synthesis, synthetic aperture radar (SAR)|
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.