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Application of SIFT algorithm in the sea ice image matching

机译:SIFT算法在海冰图像匹配中的应用

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In order to meet the needs of the marine development and maritime disaster reduction work, it is necessary to strengthen the monitoring and forecasting of sea ice. Doing sea ice drift detection can provide accurate field data for the numerical prediction of North Sea and medium-range forecasts, which is an effective way to improve forecast accuracy and reducing ice disasters. Use feature point extraction algorithm and image matching algorithm to study the ice drift speed and direction extraction method, which is the preparation of sea ice drift monitoring technology research. In many image matching algorithms, SIFT algorithm has good scale invariance of rotation, spatial rotation invariance and strong matching ability. SIFT and its extension algorithm has been proved to be the robust in the same descriptor, which is currently a hot research at home and abroad. This paper introduces four main steps of the SIFT algorithm and its application in the sea ice image matching feature points.
机译:为了满足海洋发展和海上减灾工作的需求,有必要加强海冰的监测和预测。进行海冰漂移检测可以为北海和中等预报的数值预测提供准确的现场数据,这是提高预测准确性和减少冰灾害的有效途径。使用特征点提取算法和图像匹配算法研究冰漂移速度和方向提取方法,即海冰漂移监测技术研究的制备。在许多图像匹配算法中,SIFT算法具有旋转,空间旋转不变性和强大匹配能力的良好规模不变性。 SIFT及其扩展算法已被证明是在同一描述符中的强大,目前是国内外的热门研究。本文介绍了SIFT算法的四个主要步骤及其在海冰图像匹配特征点中的应用。

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