Journal article
High-gradient pattern image velocimetry (HGPIV)
Advances in water resources, Vol.159, p.104092
01/2022
DOI: 10.1016/j.advwatres.2021.104092
Abstract
•Concepts of Image Velocimetry (Image Velocimetry) techniques are reviewed for la ying out the ground of a new IV hybrid.•The High-gradient pattern IV (HGPIV) is proposed by combining cross-correlation.•and optical flow methods for improving the IV performance and reduce the compu tational time.•HGPIV is successfully tested on a series of repeated bathymetric maps acquired w ith multi-beam echo-sounder in a natural river.
We present a new Image Velocimetry (IV) hybrid that estimates vector fields from images with widely different visualization pattern sizes such as those encountered in riverine bedform migration. The IV approach is obtained by complementing the Cross-correlation Method (CCM) with algorithms of Optical Flow Methods (OFM). The OFM procedures are first applied to automatically determine the optimal Search Windows (SWs) over the whole imaged area. Subsequently, the CCM utilized the established SWs to locally resolve velocity fields associated with the bedform movement. The new approach, labeled herein as High-Gradient Pattern IV (HGPIV), combines the advantages of both parent techniques to improve the accuracy and spatial resolution of the resultant global velocity field and significantly reduces the computational time. The HGPIV validation consists of comparing its results with those obtained with the CCM approaches applied for estimating the velocity field associated with bedform migration in a large river.
Details
- Title: Subtitle
- High-gradient pattern image velocimetry (HGPIV)
- Creators
- Hojun You - Wrexham UniversityDongsu Kim - Dankook UniversityMarian Muste - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Advances in water resources, Vol.159, p.104092
- DOI
- 10.1016/j.advwatres.2021.104092
- ISSN
- 0309-1708
- eISSN
- 1872-9657
- Publisher
- Elsevier Ltd
- Grant note
- DOI: 10.13039/501100003565, name: Ministry of Land, Infrastructure and Transport, award: 21AWMP- B121092–06; DOI: 10.13039/501100007694, name: Korea Agency for Infrastructure Technology Advancement; DOI: 10.13039/100000001, name: National Science Foundation, award: EAR 1948944; DOI: 10.13039/100000203, name: U.S. Geological Survey
- Language
- English
- Date published
- 01/2022
- Academic Unit
- IIHR--Hydroscience and Engineering; Geographical and Sustainability Sciences
- Record Identifier
- 9984460326302771
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