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Flow field image self-adaption motion vector estimating method based on FHT-CC

A technology of FHT-CC and motion vector, which is applied in image analysis, image data processing, calculation, etc., can solve the problems that are difficult to meet, the impact of window scale measurement accuracy is relatively sensitive, and tracers are not considered, so as to reduce the amount of calculation, The effect of improving spatial resolution and increasing the accuracy of displacement estimation

Inactive Publication Date: 2014-05-14
HOHAI UNIV
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Problems solved by technology

In addition, since the frequency domain correlation matching adopts a fixed observation window and does not consider the tracers entering and exiting the analysis area, the impact of the window scale on the measurement accuracy is relatively sensitive
At present, the adaptive window selection method in PIV uses the correlation coefficient as the iteration condition, and requires the number of particles in the analysis area to be more than 8 to 15 to ensure that the correlation coefficient of the effective matching remains stable, which is usually difficult to satisfy in river water surface images

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[0038] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0039] Such as figure 1 It is a schematic flow chart of the present invention, a flow field image adaptive motion vector estimation method based on FHT-CC, the method comprises the following steps:

[0040] Step 1: First obtain a flow field image, after a period of time, obtain another flow field image, convert the signals of the two flow field images into the Fourier frequency domain form, the previous frame image and the next frame The length of time between frame images depends on the specific situation.

[0041] Step 2: Use the two-dimensional Hartley transform cross-correlation (FHT-CC) to calculate the frequency domain correlation measure of the above two flow field images, and obtain the spatial domain correlation surface through inverse transformation. First, Hartley transform is performed on the Fourier frequency domain form F(u,...

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Abstract

The invention discloses a flow field image self-adaption motion vector estimating method based on FHT-CC. Firstly, a flow field image is obtained, another flow field image is obtained after a certain time period and signals of the two flow field images are converted into Fourier frequency domain manners; secondly, the frequency domain correlation measure of the two flow filed images are calculated by means of two-dimension Hartley conversion cross-correlation and an air domain correlation curved face is obtained through inverse transformation; thirdly, a Gaussian curve equation is used for fitting sub-pixel coordinates of the peak value of the air domain correlation curve face which is obtained in the first step; finally, a window scale research zone is determined. In the zone, the self-adaption window selecting technology is adopted for searching for local peak values of the SNRs of the correlation curve faces to obtain the optimal window scale. Under the optimal window scale, the coordinates of the peak value of the correlation curve faces obtained in the second step serve as motion vectors of the flow field images. According to the flow field image self-adaption motion vector estimating method based on the FHT-CC, the FHT-CC serves as the correlation measure, the equivalence and the completeness of the correlation curve faces are maintained and at the same time, the calculated amount is greatly downsized.

Description

technical field [0001] The invention relates to an FHT-CC-based self-adaptive motion vector estimation method for flow field images, belonging to the technical field of non-contact instantaneous full-field flow velocity measurement. Background technique [0002] In the past two decades, a group of outstanding scientists such as Adrian and Merzkirch have conducted in-depth research on the realization and application of particle image velocimetry (PIV), a non-contact instantaneous full-field flow velocity measurement technology, making particle image velocimetry from The principle becomes an applicable technology, which greatly improves the measurement capability of various complex flows in the laboratory environment. So far, in the two-dimensional full-field speed measurement technology, PIV is the most mature new technology, which has quickly become the standard method of speed measurement, and its products have also entered the market (American TSI Company, Aerometrics Comp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 严锡君王玲玲严妍张家华孙桐卜旸郁麟玉赵光辰
Owner HOHAI UNIV
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