Adaptive river flow measurement method based on spatiotemporal image velocimetry and optical flow

Jianping Wang, Yingbo Chen, Guangqiang Yao, Neng Li
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Abstract

This paper proposes an adaptive river discharge measurement method based on spatiotemporal image velocimetry (STIV) and optical flow to solve the problem of blurred texture features and limited measurement accuracy under complex natural environmental conditions. Optical flow tracking generates spatiotemporal images by following the flow mainstream direction of rivers with both regular and irregular natural banks. A texture similarity function filtering method effectively enhances spatiotemporal texture features. The proposed method is applied to a natural river, with measurement results from a propeller-type current meter used as truth values. It is evaluated and compared with three other methods regarding measurement accuracy, error, and other evaluation indices. The results demonstrate that the method significantly improves spatiotemporal image quality. Its estimation outcomes perform better across all evaluation metrics, enhancing the adaptability and accuracy of the flow measurement method.
基于时空图像测速和光流的自适应河流流量测量方法
本文提出了一种基于时空图像测速(STIV)和光流的自适应河流流量测量方法,以解决复杂自然环境条件下纹理特征模糊和测量精度有限的问题。光流跟踪通过跟踪具有规则和不规则自然河岸的河流主流方向生成时空图像。纹理相似性函数滤波方法可有效增强时空纹理特征。将所提出的方法应用于自然河流,并以螺旋桨式流速仪的测量结果作为真值。在测量精度、误差和其他评价指标方面,该方法与其他三种方法进行了评估和比较。结果表明,该方法显著提高了时空图像质量。其估算结果在所有评价指标上都表现更佳,从而提高了流量测量方法的适应性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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