基于海面可见光图像的海界线快速检测

针对海面运动载体的可见光序列图像，紧密结合海面图像的特点，提出了一种适用于海天背景和海岸背景的海界线检测方法。根据量化子图像的区域复杂度以及单元区域上下邻域的灰度差异，来判断海界线区域是否存在，若存在则预测海界线区域的位置，若不存在则放弃后续处理。由于海界线是自然视野中最长的连续性最好的直线，所以先利用周围纹理抑制的改进Canny算子提取轮廓边缘，然后对Hough变换进行投票加权，精细检测水平或倾斜的海界线。实验证明，该方法能够快速定位海界线区域，并得出既包含有效信息又大幅缩减了无意义信息的二值图像，可在轮廓边缘中准确找到海界线，具有很好的稳健性和实时性，可以应用于需要精确的海界线信息的工程任务中。

Fast Detection of Sea Line Based on the Visible Characteristics of Marine Images

A feasible method combining the characteristics of marine visible image is proposed to detect sea-line in the sequential images from surface vehicle. It is not only appropriate for sea-sky background but also for offshore background. The complexity of sub-images and the average gray difference of their up and down neighborhoods are measured to predict the sea-line region and the consequent processing of images without the existent of sea-line region is given up. Since the sea-line is the longest line with best continuity in the whole nature vision, improved Canny edge detection with surround texture suppression is applied to extract the contour of the object ready for line detection. Weighted vote in Hough transforming is introduced to pick the right line which is horizontal or tilted. The experimental results prove that this method can locate the sea-line region fast and obtain the binary image including the necessary information and attenuating meaningless information. Sea line can be found precisely in the contour edge. It is robust and real-time and is competent for real task where the correct sea-line location is needed.