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

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...

AI Technical Summary

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

Images