An Optical Flow-Based Approach for Minimally Divergent Velocimetry Data Interpolation

Kanberoglu, Berkay; Das, Dhritiman; Nair, Priya; Turaga, Pavan

doi:10.1155/2019/9435163

Cited by 3 publications

(3 citation statements)

References 54 publications

(41 reference statements)

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“…O. O. Akanni, et al [15], a relation between the NS equations and the isophote (level line) direction of the image is presented and authors propose to simulate a propagation of carbonate matrix to seal the interpolating domain. Another connected article is introduced in [16]. Authors minimize the divergence to develop optical flow functions.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of color image interpolation based on incompressible Navier Stokes technique

Jittawiriyanukoon¹,

Srisarkun²

2021

Bulletin EEI

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Color image interpolation encompasses reconstructing parts of a video or an image based on information from the neighbor. Technique involves the restoration of noised photos and animation or image denoising. The Navier-Stokes (NS) technique has been widely investigated as an essential research by image restoration. These NS equations contribute spectacular results for producing an animation as they augment reality. They can boost real-time video games to be more sensible than ever. In this paper, we present the Incompressible NS approach (INS) for color image interpolating. The method per se is based on fluid flow concept to circulate directed lines from the peripheral into the area to be interpolated. The image intensity represents stream function in a computational flow of 2D fluid dynamics. The algorithm is implemented to carry on lines regarding gradient vectors at the edge of the interpolating region. It uses the improvement of powerful numerical analysis. It is also proven as an innovative idea for easing problems in image analytics as well as computer vision.

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Section: Introductionmentioning

confidence: 99%

Evaluation of color image interpolation based on incompressible Navier Stokes technique

Jittawiriyanukoon¹,

Srisarkun²

2021

Bulletin EEI

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“…Over the last 20 years, different methods for addressing the point-matching problem have been proposed. Methods and techniques based on the analysis and optimization of the invariant descriptors [12][13][14], estimation of affine transformations/homographies/perspective transformations [15][16][17], epipolar geometry analysis [18][19][20], optical flow-based methods [21,22], and methods based on geometric and photometric constraints [4,23] are some of the approaches already explored.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Point-Matching Method Based on Multiple Geometrical Hypotheses

et al. 2021

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Point matching in multiple images is an open problem in computer vision because of the numerous geometric transformations and photometric conditions that a pixel or point might exhibit in the set of images. Over the last two decades, different techniques have been proposed to address this problem. The most relevant are those that explore the analysis of invariant features. Nonetheless, their main limitation is that invariant analysis all alone cannot reduce false alarms. This paper introduces an efficient point-matching method for two and three views, based on the combined use of two techniques: (1) the correspondence analysis extracted from the similarity of invariant features and (2) the integration of multiple partial solutions obtained from 2D and 3D geometry. The main strength and novelty of this method is the determination of the point-to-point geometric correspondence through the intersection of multiple geometrical hypotheses weighted by the maximum likelihood estimation sample consensus (MLESAC) algorithm. The proposal not only extends the methods based on invariant descriptors but also generalizes the correspondence problem to a perspective projection model in multiple views. The developed method has been evaluated on three types of image sequences: outdoor, indoor, and industrial. Our developed strategy discards most of the wrong matches and achieves remarkable F-scores of 97%, 87%, and 97% for the outdoor, indoor, and industrial sequences, respectively.

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“…That is, the divergence constraint attempts to minimize divergence in interpolated velocimetry data, not the divergence of the optical flow field. To our knowledge, using divergence in this way as a constraint in an optical-flow framework for image interpolation has not been investigated prior to the preliminary work presented in [57]. The method is applied to PIV, computational fluid dynamics (CFD), and analytical data and results indicate that the trade-off between minimizing errors in velocity magnitude values and errors in divergence can be managed such that both are decreased below levels observed for standard truncated sinc function-based interpolators, as well as pure optical flow-based interpolators.…”

Section: Introductionmentioning

confidence: 99%

An optical flow-based approach for the interpolation of minimally divergent velocimetry data

Kanberoglu

Nair

2017

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

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Three-dimensional (3D) biomedical image sets are often acquired with in-plane pixel spacings that are far less than the out-of-plane spacings between images. 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.

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An Optical Flow-Based Approach for Minimally Divergent Velocimetry Data Interpolation

Cited by 3 publications

References 54 publications

Evaluation of color image interpolation based on incompressible Navier Stokes technique

Evaluation of color image interpolation based on incompressible Navier Stokes technique

An Efficient Point-Matching Method Based on Multiple Geometrical Hypotheses

An optical flow-based approach for the interpolation of minimally divergent velocimetry data

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