A Semi-Automatic Approach for Estimating Bedrock and Surface Layers from Multichannel Coherent Radar Depth Sounder Imagery

The dynamic responses of the polar ice sheets in Greenland and Antarctica can have substantial impacts on sea level rise. Understanding the mass balance requires accurate assessments of the bedrock and surface layers, but identifying each layer is performed subjectively by time-consuming, dense hand selection. We have developed an approach for semi-automatically estimating bedrock and surface layers from radar depth sounder imagery acquired from Antarctica. Our solution utilizes an active contours method (“level sets”) to propagate an initial estimation of a layer’s position based upon curvature and image intensity gradients. This allows the initial curve to gravitate with topological changes while providing smooth boundaries for discriminating between bedrock and surface layers. We evaluated the proposed semi-automatic method on 20 images with respect to hand labeled ground-truth. Compared to an automatic technique, our approach reduced labeling error by factors of 5 and 3.5 for tracing bedrock and surface layers, respectively.