IceSynth: An Image Synthesis System for Sea-Ice Segmentation Evaluation

An ongoing challenge in automatic sea-ice monitoring using synthetic aperture radar (SAR) is the automatic segmentation of SAR sea-ice images based on the underlying ice type. Given the intractability of obtaining ground-truth segmentation data from polar regions, the evaluation of automatic SAR sea-ice image segmentation algorithms is generally limited to tests using real SAR imagery based on pseudo-ground truth data (e.g., manual segmentations) and simple synthetic tests using basic shape primitives. As such, it is difficult to evaluate automatic segmentation algorithms in a systematic and reliable manner using realistic scenarios. To tackle this issue, a novel image synthesis system named IceSynth is presented, which is capable of generating a variety of synthetic sea-ice images that are representative of real SAR sea-ice imagery. In IceSynth, SAR seaice textures for each ice type are synthesized via stochastic sampling based on non-parametric local conditional texture probability...

• Type: Conference
• Year: 2009
• Where: CRV
• Authors: Alexander Wong, Wen Zhang, David A. Clausi
• Keywords: CRV 2009, Robotics, SAR Sea-ice, Sar Sea-ice Image, SAR Sea-ice Imagery