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The resultant anisotropy, which can be detrimental in many applications, can be decreased using image interpolation. Optical flow and\/or other registration-based interpolators have proven useful in such interpolation roles in the past. When acquired images are comprised of signals that describe the flow velocity of fluids, additional information is available to guide the interpolation process. In this paper, we present an optical-flow based framework for image interpolation that also minimizes resultant divergence in the interpolated data.<\/jats:p>","DOI":"10.1155\/2019\/9435163","type":"journal-article","created":{"date-parts":[[2019,2,3]],"date-time":"2019-02-03T23:36:36Z","timestamp":1549236996000},"page":"1-14","source":"Crossref","is-referenced-by-count":1,"title":["An Optical Flow-Based Approach for Minimally Divergent Velocimetry Data Interpolation"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-9008-2887","authenticated-orcid":true,"given":"Berkay","family":"Kanberoglu","sequence":"first","affiliation":[{"name":"School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, 85281, USA"}]},{"given":"Dhritiman","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Technical University of Munich, Munich, 80333, 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