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Automated processing of oceanic bubble images for measuring bubble size distribution underneath breaking waves

机译:自动处理海洋气泡图像,用于测量破碎波下的气泡大小分布

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摘要

Accurate in situ measurements of oceanic bubble size distributions beneath breaking waves are needed for a better understanding of air–sea gas transfer and aerosol production processes. To achieve this goal, a novel high-resolution optical instrument for imaging oceanic bubbles was designed and built in 2013 for the High Wind Gas Exchange Study (HiWinGS) campaign in the North Atlantic Ocean. The instrument is able to operate autonomously and can continuously capture high-resolution images at 15 frames per second over an 8-h deployment. The large number of images means that it is essential to use an automated processing algorithm to process these images. This paper describes an automated algorithm for processing oceanic images based on a robust feature extraction technique. The main advantages of this robust algorithm are it is significantly less sensitive to the noise and insusceptible to the background changes in illumination, can extract circular bubbles as small as one pixel (approximately 20 ?m) in radius accurately, has low computing time (approximately 5 seconds per image), and is simple to implement. The algorithm was successfully used to analyze a large number of images (850 000 images) from deployment in the North Atlantic Ocean as part of the HiWinGS campaign in 2013.
机译:为了更好地了解海气交换和气溶胶生产过程,需要对破波之下的海洋气泡尺寸分布进行准确的原位测量。为了实现这一目标,2013年为北大西洋高风气交换研究(HiWinGS)活动设计并制造了一种新颖的高分辨率光学仪器,用于成像海洋气泡。该仪器能够自主运行,并且可以在8小时的部署中以每秒15帧的速度连续捕获高分辨率图像。大量的图像意味着必须使用自动处理算法来处理这些图像。本文介绍了一种基于鲁棒特征提取技术的自动算法,用于处理海洋图像。这种鲁棒算法的主要优点是它对噪声的敏感度大大降低,并且对照明的背景变化不敏感,可以精确地提取半径仅为一个像素(约20 µm)的圆形气泡,并且计算时间较短(约每个图片5秒),并且易于实现。作为2013年HiWinGS活动的一部分,该算法已成功用于分析北大西洋部署的大量图像(850 000张图像)。

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