Analysis of the Velocity Field of CMEs Using Optical Flow Methods

2006 ◽  
Vol 652 (2) ◽  
pp. 1747-1754 ◽  
Author(s):  
Robin C. Colaninno ◽  
Angelos Vourlidas
Keyword(s):  
Velocity Field ◽  
Optical Flow

scholarly journals Optimization algorithm of the velocity field determining in image processing

2018 ◽  
pp. 174-181
Author(s):  
Pavel Bazhanov ◽  
Elena Kotina ◽  
Dmitri Ovsyannikov ◽  
Victor Ploskikh
Keyword(s):  
Image Processing ◽  
Velocity Field ◽  
Optical Flow ◽  
Optimization Algorithm ◽  
Integral Functional ◽  
Gradient Methods ◽  
Analytical Representation

The paper proposes a new algorithm for constructing the velocity field, which is based on the study of the integral functional on the ensemble of trajectories. The resulting analytical representation of the variation of the integral functional gives us the gradient of the investigated functional. It allows to find the desired parameters using gradient methods, which determine the velocity field. This approach allows both optical flow and non-optical flow construction. The proposed algorithm can be used in the analysis of various images, in particular in radionuclide image processing.

Optical Flow Based Velocity Field Control

2008 ◽  
pp. 771-781 ◽  
Author(s):  
Leonardo Fermín ◽  
Wilfredis Medina-Meléndez ◽  
Juan C. Grieco ◽  
Gerardo Fernández-López
Keyword(s):  
Velocity Field ◽  
Optical Flow ◽  
Field Control

Structure-preserving Interpolation of Temporal and Spatial Image Sequences Using an Optical Flow-based Method

2007 ◽  
Vol 46 (03) ◽  
pp. 300-307 ◽  
Author(s):  
D. Säring ◽  
H. Handels ◽  
J. Ehrhardt
Keyword(s):  
Velocity Field ◽  
Optical Flow ◽  
Temporal Resolution ◽  
Interpolation Method ◽  
Image Data ◽  
Image Sequences ◽  
Registration Method ◽  
Structure Preserving ◽  
Spatial Image ◽  
Temporal And Spatial

Summary Objectives: Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. Methods: In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. Results: The behaviorand capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. Conclusions: The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

An Algorithm for Optical Flow Computation Based on a Quasi-Interpolant Operator

2006 ◽  
Vol 2 (1-2) ◽  
pp. 93-106 ◽  
Author(s):  
E. Francomano ◽  
C. Lodato ◽  
S. Lopes ◽  
A. Tortorici
Keyword(s):  
Velocity Field ◽  
Flow Field ◽  
Optical Flow ◽  
Linear Systems ◽  
Apparent Motion ◽  
Fundamental Problem ◽  
Image Sequences ◽  
Spline Functions ◽  
Flow Computation ◽  
Optical Flow Computation

A fundamental problem in the processing of image sequences is the computation of the velocity field of the apparent motion of brightness patterns usually referred to optical flow. In this paper a novel optical flow estimator based on a bivariate quasi-interpolant operator is presented. Namely, a non linear minimizing technique has been employed to compute the velocity vectors by modeling the flow field with a 2D quasi-interpolant operator based on centered cardinal B-spline functions. In this way an efficient computational scheme for optical flow estimate is provided. In addition the large solving linear systems involved in the process are sparse. Experiments on several image sequences have been carried out in order to investigate the performance of the optical flow estimator.

Application of L-K Optical Flow Algorithm Mixed with Pyramid on Calculating Water Surface Flow Field

2013 ◽  
Vol 333-335 ◽  
pp. 897-903 ◽  
Author(s):  
Zhao Hui Han ◽  
Yan Feng Wang
Keyword(s):  
Velocity Field ◽  
Flow Field ◽  
Optical Flow ◽  
Water Surface ◽  
Image Sequence ◽  
Surface Flow ◽  
Aperture Problem ◽  
Wind Speeds ◽  
Gaussian Pyramid ◽  
Flow Algorithm

A classical Lucas-Kanade optical flow algorithm was used to analysis the IR Image sequence of the wind-driven surface in this paper. Gaussian pyramid representation was introduced to retain both detail components and veracity for velocity field when considering the aperture problem and robustness. Three layers of pyramid for L-K optical flow is the best comparing with other layers (from one to four) in property. L-K optical flow algorithm mixed with pyramid representation shown an qualified power on calculating water surface flow field, demonstrated by optical flow fields on different wind speeds ( from 3m/s to 6m/s).

scholarly journals A Novel Technique for Moving Object Detection & Tracking with Optical Flow

2019 ◽  
Vol 8 (4) ◽  
pp. 5182-5188
Keyword(s):  
Velocity Field ◽  
Object Detection ◽  
Optical Flow ◽  
Short Duration ◽  
Processing Time ◽  
Flow Analysis ◽  
Novel Technique ◽  
Quality Detection ◽  
Integral Images ◽  
Novel Algorithm

A novel technique for tracking for tracking of objects in moving state is proposed to done by optical flow analysis which provide accurate results. In this Optical flow analysis, the velocity vectors of the pixels are obtained. As a result, velocity field is analyzed for the frame sequences which are considered and described for short duration of the video. This method doesn’t need to refer the previous frames which reduces the processing time and can be applicable for real time events. This novel algorithm produces better results with repeatability, uniqueness and reliability, compared to previous techniques. This method can be able to perform faster computation and comparison. This can be achieved by performing image convolutions for integral images followed by technical operations in the descriptors and detectors. Finally these methods can be simplified to the needed requirements. This leads to a package of better quality detection followed by description and recognition steps. The paper encircles a brief explanation of the algorithm and the results of simulation are also described in detail.

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