Roughness Change Analysis of Sea Surface From Visible Images by Fractals

This paper presents an analysis of sea surface roughness from visible images based on fractals features for the first time. We measure fractal dimensions of sea surface images by the methods of box counting, fractional Brownian motion, and area measurement. The empirical values of sea surface roughness are found from measured wind speed and an empirical relation. The correlations between wind speeds (or sea surface roughness) and fractal dimensions are evaluated based on the data from a field experiment. Further, four types of noises with different parameters are introduced to the sea surface images. Then noise suppression performances of six methods are evaluated. Our experiments have demonstrated that our fractal methods and empirical relation between wind speeds and fractal dimensions are effective for analyzing roughness changes of sea surface from visible images.