Automated measurements of whitecaps on the ocean surface from a buoy-mounted camera

We quantify the percentage of sea surface covered by whitecaps from images taken by a non-stationary camera mounted on a moored buoy using an Adaptive Thresholding Segmentation (ATS) method and an Iterative Between Class Variance (IBCV) approach. In the ATS algorithm, the optimal value for the threshold is determined as the last inflection point of the smoothed cumulative histogram of the scene. This makes the method more effective in finding the optimal value of the threshold and reduces the computational efforts compared to the conventional Automated Whitecap Extraction (AWE) technique. In the IBCV method, the optimum criterion for determining the value of the threshold corresponds to the measure of separability between the segmented water and whitecap pixels. In our experiments, the fraction of each image covered by the whitecap is determined using the aforementioned dynamical thresholding techniques for images taken under complex forcing and lighting conditions. Comparisons between different techniques suggest the effectiveness of the proposed methodologies, in particular the ATS algorithm to separate the whitecap features from the darker water pixels.