CN110223328A - A kind of improvement particle image velocimetry robustness optical flow approach based on physics - Google Patents
A kind of improvement particle image velocimetry robustness optical flow approach based on physics Download PDFInfo
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Abstract
The improvement particle image velocimetry robustness optical flow approach based on physics that the invention discloses a kind of, includes the following steps: the building of S1, steady energy functional；S2, the building for checking data item；The selection of S3, smooth item；The building of S4, penalty；S5, the processing of model energy functional minimization；S6, optical flow computation；The present invention provides a kind of improvement particle image velocimetry robustness optical flow approach based on physics, and present invention encompasses the buildings of steady energy functional；Check the building of data item；The selection of smooth item；The building of penalty；The processing of model energy functional minimization；Optical flow computation loose particles image speed measurement robustness is high；In the present invention further in the building process of the steady energy functional, the optical flow constraint equation based on physics is constructed first；Then change for optical flow constraint equation partial differential；Last to generate steady energy functional according to result of variations, energy functional versatility is high.
Description
Technical field
The invention belongs to Particle Image Velocimetry field, specially a kind of improvement particle image velocimetry based on physics
Robustness optical flow approach.
Background technique
Particle image velocimetry is that a kind of use repeatedly images to record the position of particle in flow field, and analyzes the image taken the photograph,
Method to measure flowing velocity.The new development tradition FLOW VISUALIZATION for being substantially Flow visualisation technology is Experimental Flowing Object power
The important component learned, its main task is that certain properties of flowing are subject to visual representation, to obtain to flowing
All-round developing understanding is obtained, because having formed a flourishing long time project in experimental fluid mechanics；
For application aspect, fluid velocity field measurement is for understanding complicated stream in hydrodynamics and aerodynamic studies
Body is of great significance.Fluid motion is a kind of typical non-rigid motion, and calculating need to be based on image processing techniques.It can pass through
Partial fluid motion vector size, direction and distribution situation are obtained to dynamic image sequence analysis, and then can be obtained such as sticky
And the physical characteristics such as vortex field distribution.Under normal conditions, due to moving object is transparent or not easily pass through optical device observation, need by
Visible particles are placed in measured object, and to obtain fluid motion feature indirectly by estimation particle motion vector, this calls particle picture
It tests the speed.
However traditional particle image velocimetry optical flow approach, robustness is poor, optical flow computation low efficiency and accuracy is undesirable,
For this purpose, we are proposed a kind of improvement particle image velocimetry robustness optical flow approach based on physics.
Summary of the invention
It is an object of the invention to: in order to solve traditional particle image velocimetry optical flow approach, robustness is poor, optical flow computation
Low efficiency and the undesirable technical problem of accuracy, provide a kind of improvement particle image velocimetry robustness light stream based on physics
Method.
The technical solution adopted by the invention is as follows:
A kind of improvement particle image velocimetry robustness optical flow approach based on physics, includes the following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Wherein, in the S3 smooth item selection, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
Wherein, in the S4 penalty building, the specific steps of which are as follows:
S401, secondary penalty is introduced；
The full variation transformation of S402, secondary penalty；
S403, robust variation penalty is obtained.
Wherein, model energy functional minimization is handled in the S5, the specific steps of which are as follows:
S501, basic minimization algorithm equation is introduced；
S502, robust variation penalty is imported；
S503, overrelaxation iterative calculation obtain optical flow field.
Wherein, optical flow computation in the S6, the specific steps of which are as follows:
S601, optical flow field is layered using pyramid decimation factor；
S602, up-sampling interpolation calculation；
S603, image transformation and inter-layer data processing are approached using linearisation.
Wherein, the pyramid decimation factor value range is 0.9~0.95.
Wherein, the up-sampling interpolation calculation is calculated using bicubic interpolation.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
1, the present invention provides a kind of improvement particle image velocimetry robustness optical flow approach based on physics, and the present invention covers
The building of steady energy functional；Check the building of data item；The selection of smooth item；The building of penalty；Model energy is general
The processing of letter minimization；Optical flow computation loose particles image speed measurement robustness is high.
2, in the present invention further in the building process of the steady energy functional, light of the building based on physics first
Flow constraint equation；Then change for optical flow constraint equation partial differential；It is last to generate steady energy functional, energy according to result of variations
It is high to measure functional versatility.
3, secondary penalty is firstly introduced into further in the building process of the penalty in the present invention；Then
The full variation of secondary penalty converts；Finally obtain robust variation penalty, penalty high treating effect.
4, in the present invention further during the optical flow computation, first with pyramid decimation factor to optical flow field point
Layer；Then up-sampling interpolation calculation；Image transformation finally is approached using linearisation and inter-layer data is handled；The wherein pyramid
Decimation factor value range is 0.9~0.95；The up-sampling interpolation calculation is calculated using bicubic interpolation；Computational efficiency it is high and
Accuracy is high.
Detailed description of the invention
Fig. 1 is process simplified schematic diagram of the invention；
Fig. 2 is the process simplified schematic diagram of the building of steady energy functional in the present invention；
Fig. 3 is the process simplified schematic diagram that the building of data item is checked in the present invention；
Fig. 4 is the process simplified schematic diagram of the selection of smooth item in the present invention；
Fig. 5 is the process simplified schematic diagram of the building of penalty in the present invention；
Fig. 6 is the process simplified schematic diagram of model energy functional minimization processing in the present invention；
Fig. 7 is the process simplified schematic diagram of optical flow computation in the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
In the description of the present invention, it should be noted that term " center ", "upper", "lower", "left", "right", "vertical",
The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely to
Convenient for description the present invention and simplify description, rather than the device or element of indication or suggestion meaning must have a particular orientation,
It is constructed and operated in a specific orientation, therefore is not considered as limiting the invention；Term " first ", " second ", " third "
It is used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance；In addition, unless otherwise specific regulation and limit
Fixed, term " installation ", " connected ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, be also possible to detachably connect
It connects, or is integrally connected；It can be mechanical connection, be also possible to be electrically connected；It can be directly connected, intermediate matchmaker can also be passed through
Jie is indirectly connected, and can be the connection inside two elements.It for the ordinary skill in the art, can be with concrete condition
Understand the concrete meaning of above-mentioned term in the present invention.
Embodiment one, referring to Fig.1~3, a kind of improvement particle image velocimetry robustness optical flow approach based on physics, packet
Include following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Embodiment two, referring to Fig.1~4, a kind of improvement particle image velocimetry robustness optical flow approach based on physics, packet
Include following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Wherein, in the S3 smooth item selection, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
Embodiment three, referring to Fig.1~5, a kind of improvement particle image velocimetry robustness optical flow approach based on physics, packet
Include following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Wherein, in the S3 smooth item selection, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
Wherein, in the S4 penalty building, the specific steps of which are as follows:
S401, secondary penalty is introduced；
The full variation transformation of S402, secondary penalty；
S403, robust variation penalty is obtained.
Example IV, referring to Fig.1~6, a kind of improvement particle image velocimetry robustness optical flow approach based on physics, packet
Include following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Wherein, in the S3 smooth item selection, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
Wherein, in the S4 penalty building, the specific steps of which are as follows:
S401, secondary penalty is introduced；
The full variation transformation of S402, secondary penalty；
S403, robust variation penalty is obtained.
Wherein, model energy functional minimization is handled in the S5, the specific steps of which are as follows:
S501, basic minimization algorithm equation is introduced；
S502, robust variation penalty is imported；
S503, overrelaxation iterative calculation obtain optical flow field.
Embodiment five, referring to Fig.1~7, a kind of improvement particle image velocimetry robustness optical flow approach based on physics, packet
Include following steps: the building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
Wherein, in the S1 steady energy functional building, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
Wherein, the building of data item is checked in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
Wherein, in the S3 smooth item selection, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
Wherein, in the S4 penalty building, the specific steps of which are as follows:
S401, secondary penalty is introduced；
The full variation transformation of S402, secondary penalty；
S403, robust variation penalty is obtained.
Wherein, model energy functional minimization is handled in the S5, the specific steps of which are as follows:
S501, basic minimization algorithm equation is introduced；
S502, robust variation penalty is imported；
S503, overrelaxation iterative calculation obtain optical flow field.
Wherein, optical flow computation in the S6, the specific steps of which are as follows:
S601, optical flow field is layered using pyramid decimation factor；
S602, up-sampling interpolation calculation；
S603, image transformation and inter-layer data processing are approached using linearisation.
Wherein, the pyramid decimation factor value is 0.9；Wherein, the up-sampling interpolation calculation is inserted using bicubic
Value calculates.
Working principle: the present invention provides a kind of improvement particle image velocimetry robustness optical flow approach based on physics, this
Invention covers the building of steady energy functional；Check the building of data item；The selection of smooth item；The building of penalty；Mould
The processing of type energy functional minimization；Optical flow computation loose particles image speed measurement robustness is high；Further described steady in the present invention
In the building process of strong energy functional, the optical flow constraint equation based on physics is constructed first；Then it is directed to optical flow constraint equation
Partial differential variation；Last to generate steady energy functional according to result of variations, energy functional versatility is high；Further exist in the present invention
In the building process of the penalty, it is firstly introduced into secondary penalty；The then full variation transformation of secondary penalty；Most
Robust variation penalty, penalty high treating effect are obtained afterwards；In the present invention further during the optical flow computation,
Optical flow field is layered first with pyramid decimation factor；Then up-sampling interpolation calculation；Finally image is approached using linearisation
Transformation and inter-layer data processing；Wherein the pyramid decimation factor value range is 0.9~0.95；The up-sampling interpolation meter
It calculates and is calculated using bicubic interpolation；Computational efficiency is high and accuracy is high.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (9)
1. a kind of improvement particle image velocimetry robustness optical flow approach based on physics, characterized by the following steps:
The building of S1, steady energy functional；
S2, the building for checking data item；
The selection of S3, smooth item；
The building of S4, penalty；
S5, the processing of model energy functional minimization；
S6, optical flow computation.
2. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as described in claim 1, feature
It is: the building of steady energy functional in the S1, the specific steps of which are as follows:
S101, optical flow constraint equation of the building based on physics；
S102, change for optical flow constraint equation partial differential；
S103, steady energy functional is generated according to result of variations.
3. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as claimed in claim 2, feature
It is: checks the building of data item in the S2, the specific steps of which are as follows:
S201, luminance picture data are obtained；
S202, gradient image data are obtained；
S203, color difference image data are obtained；
S204, the complex light stream data model for constructing brightness, gradient and color difference.
4. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as claimed in claim 3, feature
It is: the selection of smooth item in the S3, the specific steps of which are as follows:
S301, global smoothing model building；
The verifying and amendment of S302, global smoothing model.
5. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as described in claim 1, feature
It is: the building of penalty in the S4, the specific steps of which are as follows:
S401, secondary penalty is introduced；
The full variation transformation of S402, secondary penalty；
S403, robust variation penalty is obtained.
6. a kind of improvement particle image velocimetry robustness optical flow approach based on physics a method as claimed in any one of claims 1 to 5,
It is characterized by: model energy functional minimization is handled in the S5, the specific steps of which are as follows:
S501, basic minimization algorithm equation is introduced；
S502, robust variation penalty is imported；
S503, overrelaxation iterative calculation obtain optical flow field.
7. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as claimed in claim 6, feature
It is: optical flow computation in the S6, the specific steps of which are as follows:
S601, optical flow field is layered using pyramid decimation factor；
S602, up-sampling interpolation calculation；
S603, image transformation and inter-layer data processing are approached using linearisation.
8. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as claimed in claim 7, feature
Be: the pyramid decimation factor value range is 0.9~0.95.
9. a kind of improvement particle image velocimetry robustness optical flow approach based on physics as claimed in claim 7, feature
Be: the up-sampling interpolation calculation is calculated using bicubic interpolation.
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| CN116070550A (en) * | 2023-03-07 | 2023-05-05 | 浙江大学 | Improved reconstruction flow field pressure field method based on time-resolved PIV |
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