Long-Distance Sea Wave Sparse Matching Algorithm for Sea Level Monitoring System

Benefiting from rich agricultural land, easy transport and fishing, etc., more and more people are moving to live in coastal areas, with more than 200 million people now living in coastal areas that are vulnerable to extreme sea level events. Sea level information is useful for coastal societies. Image measurement is rapidly developing as a new type of measurement tool. A multicamera-based sea level monitoring system along Japan's coast near the Pacific is proposed in this paper, and a long-distance sea wave matching method for this system is described. The whole system employs multiple binocular vision systems to take sea surface images and obtain the sea level height based on the disparity between the field of views of the left and right cameras, forming a local measurement and overall analysis monitoring system. Sea level monitoring requires a high processing accuracy and speed to realize a timely response to extreme events. Thus, the paper extracts sea waves and integrates a sea wave's appearance features as feature points and descriptors and pioneers the idea of searching deterministic features for fast image processing. The average stereo matching precision of the proposed method is up to 89.9% with a running time smaller than 40 ms for most pairs of images. Experiments on various real sea surface image pairs are conducted to validate the effectiveness of the proposed method.