CN104457615B - Three-dimension digital imaging method based on generalized S-transform - Google Patents

Abstract

The invention discloses a kind of three-dimension digital imaging method based on generalized S-transform, including：Coding is carried out to structure light and generates sinusoidal gray scale bar graph, the deformation gray scale bar graph that video camera obtains the original gradation bar graph in monoscopic and modulated by object depth information；The generalized S-transform based on energy intensity optimization and encircled energy principle is carried out, and the fundamental component of gray scale bar graph is calculated by filtering method；Inverse Fourier transform is carried out to fundamental component, then Jing takes the wrapped phase that phase angle obtains gray scale bar graph；Phase unwrapping is carried out to wrapped phase and the phase difference of original gradation bar graph and deformation gray scale bar graph is obtained according to the result of phase unwrapping；According to Fourier Transform Profilomery measuring principle and phase difference, the three-dimensional coordinate of the object to be imaged per is calculated.The present invention has the advantages that high precision and wide adaptability, can be widely applied to 3 D digital imaging and optical 3-dimensional rebuilds field.

Description

Three-dimension digital imaging method based on generalized S-transform

Technical field

The invention belongs to 3 D digital imaging and optical 3-dimensional rebuild field, generalized S-transform is based on more particularly, to a kind of Three-dimension digital imaging method.

Background technology

Application Optics is come to carry out 3 D digital imaging be an emerging ambit in recent years, and is further development of essence True three-dimensional measurement technology, which is widely used in commercial measurement, quality testing, machine vision, intelligence machine control and biomedicine All many-sides such as diagnosis.At present by object to be imaged projective structure light, solving phase information to carry out three from structure light The method of dimension word imaging mainly has Moire topography art, phase measuring profilometer and Fourier transform profilometry etc..More takes turns Wide art has used moire fringe projection, but the method cannot initiative recognition depth picture concavo-convex and phase difference be less than it is corresponding during 2 π Elevation information.Phase measuring profilometer is then needed to several structure lights of project objects, then by phase shift algorithm calculating depth , as the phase value of every bit, computationally intensive, time-consuming for degree.Fourier transform profilometry only need to be to project objects once (or twice) Structure light, then just can extract the phase information modulated by object height, but if being imaged using Fast Fourier Transform (FFT) Object height changes in distribution rate is big, and the algorithm cannot can accurately extract one-level frequency spectrum because of spectral aliasing, so as to cause phase place to be believed The extraction error of breath is larger.And the accuracy of the phase information extracted then directly is determined and recovers the accurate of object dimensional pattern Degree.

The advantage of adding window Fourier transformation and wavelet transformation is combined based on the phase demodulation technique of S-transformation, which is not losing sky Between information while, the contact in signal spatial domain/between time domain and frequency is set up by the form of time frequency analysis.Therefore work as signal Non-flat stability when causing the aliasing between useful fundamental frequency and other frequency contents, it is possible to use S-transformation is effectively avoided Spectral aliasing, and then solve phase information.Although in S-transformation, the shape of window can change with frequency, with good time-frequency Resolution ratio, but its window size determines by the real-time frequency of signal all the time and can not be changed with the change of frequency change rate, this Prevent S-transformation in the larger signal of processing frequency rate of change from being accurately positioned fundamental component, its solution phase precision it is not high, it is right The object adaptability for possessing different depth rate of change is not wide.

The content of the invention

In order to solve above-mentioned technical problem, the purpose of the present invention is：There is provided a kind of high precision and wide adaptability based on wide The three-dimension digital imaging method of adopted S-transformation.

The technical solution adopted for the present invention to solve the technical problems is：

Based on the three-dimension digital imaging method of generalized S-transform, including：

S1, coding is carried out to structure light generate sinusoidal gray scale bar graph, and by projector equipment by sinusoidal gray scale bar graph It is projeced in reference planes, the original gradation bar graph g in monoscopic is obtained by video camera₁(x, y), then by the object to be imaged It is positioned in reference planes, the deformation gray scale bar graph g in monoscopic by object depth information modulation is obtained by video camera₂(x, y)；

S2, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂(x, y) is carried out based on energy The generalized S-transform of amount strength optimization and encircled energy principle, and original gradation bar graph g is calculated by filtering method₁(x, Y) fundamental component f₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y)₂(x, y)；

S3, fundamental component f respectively to extracting from two width gray scale bar graphs₁(x, y) and f₂(x, y) carries out Fourier Inverse transformation, then takes phase angle to the result of inverse Fourier transform respectively, obtains original gradation bar graph g₁The parcel phase of (x, y) PositionWith deformation gray scale bar graph g₂The wrapped phase of (x, y)

S4, to wrapped phaseWithPhase unwrapping is carried out respectively obtains continuous phase distributionWithAnd the phase difference comprising object depth modulation information is obtained according to the result of phase unwrappingThe phase differenceComputing formula be：

S5, the camera parameters and Object Depth of according to Fourier Transform Profilomery measuring principle, demarcating monocular imaging system With the mapping relations of phase place change, and according to the phase difference for obtainingThe three-dimensional coordinate of the object to be imaged per is calculated, from And realize the 3 D digital imaging of the object to be imaged.

Further, step S2, which includes：

S21, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂Each traveling of (x, y) Row obtains original gradation bar graph g based on energy intensity optimization and the generalized S-transform of encircled energy principle₁(x, y) and deformation Gray scale bar graph g₂The optimal S-transformation matrix of (x, y) per a line, the definition of the generalized S-transform is：

Wherein, f is frequency, y_k=1,2 ..., y_max,g(x,y_k) represent gray scale bar graph row k, w (b-x, σ (f)) represent be centrally located at x=b and standard deviation for σ (f) Gauss function, σ (f)=1/ | f |^p, p is constant；

S22, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S of (x, y) per a line becomes The filtering that matrix carries out based on local spectrum is changed, original gradation bar graph g is obtained₁(x, y) and deformation gray scale bar graph g₂(x, y) Fundamental component per a line, then the every a line fundamental component for obtaining is overlapped in the y-direction, so as to obtain original gradation striped Figure g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two-dimentional fundamental component f of (x, y)₂(x, y).

Further, step S21, which includes：

S211, the initial value p to parameter p of Gauss function in generalized S-transform₀, iteration interval Δ p and iteration final value p_tEnter Row is arranged；

S212, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂Every a line application of (x, y) is wide Adopted S-transformation, so as to obtain every a line g of original gradation bar graph₁(x,y_k) with deformation gray scale bar graph every a line g₂(x,y_k) A series of S-transformation matrixes when parameter p takes different valueWithThe S-transformation matrixWithExpression formula be：

S213, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformations of (x, y) per a line MatrixWithMatrix " ridge " is found respectively：If a certain S-transformation matrix S_p(b, f) is at point (b, f) place Energy intensity is the absolute value of its amplitude | S_p(b, f) |, then for each spatial point b_ii, b_ii=1,2 ... ..., b_max, its energy Will be corresponding to S during amount intensity acquirement maximum_pA maximum of points in (b, f) is to (b_ii, f_ii), and own in all spatial points The set of maximum of points pair constitutes S-transformation matrix S_p" ridge " Ω (b of (b, f)_ii,f_ii)；

S214, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformations of (x, y) per a line MatrixWith" ridge " carry out the setting of energy intensity threshold value, and according to the energy intensity threshold for arranging Value carries out energy intensity optimization to S-transformation matrix, so as to obtain original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂ A series of S-transformation matrixes of (x, y) each energy intensity optimization of passing throughWith

Each S-transformation square in S215, a series of S-transformation matrixes of energy intensity optimization of passing through each to gray scale bar graph Battle array S_p(b, f), one by one Frequency point f_jjCalculate Frequency point f_jjEncircled energy CM (the f of correspondence row_jj, p), the energy is concentrated Degree CM (f_jj, expression formula p) is：

Wherein, q is constant, f_jj=1,2 ... ..., f_max；

S216, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, y) each energy intensity of passing through is excellent A series of S-transformation matrixes changedWithThis line is pieced together out most using encircled energy principle Good S-transformation matrixWith

Further, step S214, which is specially：

One unified energy intensity threshold value E is set, a series of S-transformation matrixes of the gray scale bar graph per a line are then judged In any one S-transformation matrix S_pOn " ridge " of (b, f), energy intensity minimum of a value with the ratio of energy intensity maximum on " ridge " is It is no less than E, if so, then reject this S-transformation matrix S_p(b, f), conversely, then retain, so as to obtain original gradation bar graph g₁(x, Y) with deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) each energy intensity optimization of passing throughWith

Further, step S216, which is specially：

A series of S-transformation matrix of the Jing energy intensities optimizations to gray scale bar graph per a lineOne by one frequently Rate point f_jjComparison corresponds to the encircled energy CM (f of that a line_jj, p), select the S-transformation matrix work of that row of encircled energy maximum To correspond to the optimal S-transformation matrix that a line pieces together outThe optimal S-transformation matrixMeet：

Further, step S22, which includes：

S221, according to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation of (x, y) per a line Matrix is accurately positioned to local fundamental component；

S222, according to default filtering window function, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation matrix of (x, y) per a line carries out the filtering based on local spectrum, obtains original gradation bar graph g₁(x, y) is every Capable local fundamental componentAnd deformation gray scale bar graph g₂(x, y) often capable local fundamental component

S223, the local fundamental component by two width gray scale bar graphs per a line make local fundamental component along space x-axis respectively Superposition, obtains original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y) per a line₁(x, y_k) With f₂(x, y_k)；

S224, the fundamental component f by two width gray scale bar graphs per a line₁(x, y_k) and f₂(x, y_k) folded along space y-axis respectively Plus, obtain original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two dimension of (x, y) Fundamental component f₂(x, y).

Further, step S3, which is specially：

Respectively to original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂(x, Y) two-dimentional fundamental component f₂(x, y) does inverse Fourier transform, obtains fundamental frequency complex signal C of two width gray scale bar graphs₁With C₂, so Afterwards respectively to fundamental frequency complex signal C₁With C₂Phase angle is taken, original gradation bar graph g is obtained₁The wrapped phase of (x, y)With Deformation gray scale bar graph g₂The wrapped phase of (x, y)The wrapped phaseAnd wrapped phaseMathematical expression be expressed as：

Wherein, Im [] represents the imaginary part for taking complex signal, and Re [] represents the real part for taking complex signal.

The invention has the beneficial effects as follows：To camera acquisition to gray scale bar graph carry out based on energy intensity optimize and energy The generalized S-transform of quantity set moderate principle, the window size for overcoming traditional S-transformation can not change with the change of frequency change rate Defect, accurately realize and separate between useful fundamental component and low high fdrequency component, be effectively improved phase calculation Accuracy, the object wide adaptability to possessing different depth rate of change；The inventive method only needs the single width bar graph just can be real Phase is now accurately solved, the speed of 3 D digital imaging is improve and real time dynamic measurement can be realized.

Description of the drawings

The invention will be further described with reference to the accompanying drawings and examples.

Fig. 1 is overall flow figure of the present invention based on the three-dimension digital imaging method of generalized S-transform；

Fig. 2 is the intensity profile figure that the present invention carries out the horizontal x directions of original gradation bar graph during structure light coding；

Fig. 3 is the flow chart of step S2 of the present invention；

Fig. 4 is the flow chart of step S21 of the present invention；

Fig. 5 is the flow chart of step S22 of the present invention；

Fig. 6 is the structural representation of monocular 3-D imaging system of the present invention.

Specific embodiment

With reference to Fig. 1, based on the three-dimension digital imaging method of generalized S-transform, including：

S1, coding is carried out to structure light generating sinusoidal gray scale bar graph, the intensity profile for which being obtained along x horizontal directions is as schemed Shown in 2, and sinusoidal gray scale bar graph is projeced in reference planes by projector equipment, the original in monoscopic is obtained by video camera Beginning gray scale bar graph g₁(x, y), is then positioned over the object to be imaged in reference planes, obtains thing is received in monoscopic by video camera The deformation gray scale bar graph g of body depth information modulation₂(x, y)；

S2, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂(x, y) is carried out based on energy The generalized S-transform of amount strength optimization and encircled energy principle, and original gradation bar graph g is calculated by filtering method₁(x, Y) fundamental component f₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y)₂(x, y)；

S3, fundamental component f respectively to extracting from two width gray scale bar graphs₁(x, y) and f₂(x, y) carries out Fourier Inverse transformation, then takes phase angle to the result of inverse Fourier transform respectively, obtains original gradation bar graph g₁The parcel phase of (x, y) PositionWith deformation gray scale bar graph g₂The wrapped phase of (x, y)

S4, to wrapped phaseWithPhase unwrapping is carried out respectively obtains continuous phase distributionWithAnd the phase difference comprising object depth modulation information is obtained according to the result of phase unwrappingThe phase differenceComputing formula be：

S5, the camera parameters and Object Depth of according to Fourier Transform Profilomery measuring principle, demarcating monocular imaging system With the mapping relations of phase place change, and according to the phase difference for obtainingThe three-dimensional coordinate of the object to be imaged per is calculated, from And realize the 3 D digital imaging of the object to be imaged.

With reference to Fig. 3, it is further used as preferred embodiment, step S2, which includes：

S21, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂Each traveling of (x, y) Row obtains original gradation bar graph g based on energy intensity optimization and the generalized S-transform of encircled energy principle₁(x, y) and deformation Gray scale bar graph g₂The optimal S-transformation matrix of (x, y) per a line, the definition of the generalized S-transform is：

Wherein, f is frequency, y_k=1,2 ..., y_max,g(x,y_k) represent gray scale bar graph row k, w (b-x, σ (f)) represent be centrally located at x=b and standard deviation for σ (f) Gauss function, σ (f)=1/ | f |^p, p is constant；

S22, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S of (x, y) per a line becomes The filtering that matrix carries out based on local spectrum is changed, original gradation bar graph g is obtained₁(x, y) and deformation gray scale bar graph g₂(x, y) Fundamental component per a line, then the every a line fundamental component for obtaining is overlapped in the y-direction, so as to obtain original gradation striped Figure g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two-dimentional fundamental component f of (x, y)₂(x, y).

With reference to Fig. 4, it is further used as preferred embodiment, step S21, which includes：

S211, the initial value p to parameter p of Gauss function in generalized S-transform₀, iteration interval Δ p and iteration final value p_tEnter Row is arranged；

S212, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂Every a line application of (x, y) is wide Adopted S-transformation, so as to obtain every a line g of original gradation bar graph₁(x,y_k) with deformation gray scale bar graph every a line g₂(x,y_k) A series of S-transformation matrixes when parameter p takes different valueWithThe S-transformation matrixWithExpression formula be：

S213, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformations of (x, y) per a line MatrixWithMatrix " ridge " is found respectively：If a certain S-transformation matrix S_p(b, f) is at point (b, f) place Energy intensity is the absolute value of its amplitude | S_p(b, f) |, then for each spatial point b_ii, b_ii=1,2 ... ..., b_max, its energy Will be corresponding to S during amount intensity acquirement maximum_pA maximum of points in (b, f) is to (b_ii, f_ii), and own in all spatial points The set of maximum of points pair constitutes S-transformation matrix S_p" ridge " Ω (b of (b, f)_ii,f_ii)；

S214, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformations of (x, y) per a line MatrixWith" ridge " carry out the setting of energy intensity threshold value, and according to the energy intensity threshold for arranging Value carries out energy intensity optimization to S-transformation matrix, so as to obtain original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂ A series of S-transformation matrixes of (x, y) each energy intensity optimization of passing throughWith

Each S-transformation square in S215, a series of S-transformation matrixes of energy intensity optimization of passing through each to gray scale bar graph Battle array S_p(b, f), one by one Frequency point f_jjCalculate Frequency point f_jjEncircled energy CM (the f of correspondence row_jj, p), the energy is concentrated Degree CM (f_jj, expression formula p) is：

Wherein, q is constant, f_jj=1,2 ... ..., f_max；

S216, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, y) each energy intensity of passing through is excellent A series of S-transformation matrixes changedWithThis line is pieced together out most using encircled energy principle Good S-transformation matrixWith

It is further used as preferred embodiment, step S214, which is specially：

One unified energy intensity threshold value E is set, a series of S-transformation matrixes of the gray scale bar graph per a line are then judged In any one S-transformation matrix S_pOn " ridge " of (b, f), energy intensity minimum of a value with the ratio of energy intensity maximum on " ridge " is It is no less than E, if so, then reject this S-transformation matrix S_p(b, f), conversely, then retain, so as to obtain original gradation bar graph g₁(x, Y) with deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) each energy intensity optimization of passing throughWith

It is further used as preferred embodiment, step S216, which is specially：

A series of S-transformation matrix of the Jing energy intensities optimizations to gray scale bar graph per a lineOne by one frequently Rate point f_jjComparison corresponds to the encircled energy CM (f of that a line_jj, p), select the S-transformation matrix work of that row of encircled energy maximum To correspond to the optimal S-transformation matrix that a line pieces together outThe optimal S-transformation matrixMeet：

Wherein, P_optThe optimum p value of that a line of encircled energy maximum correspondence is referred to, and a P value then determines a S Transformation matrix.

With reference to Fig. 5, it is further used as preferred embodiment, step S22, which includes：

S221, according to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation of (x, y) per a line Matrix is accurately positioned to local fundamental component；

S222, according to default filtering window function, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation matrix of (x, y) per a line carries out the filtering based on local spectrum, obtains original gradation bar graph g₁(x, y) is every Capable local fundamental componentAnd deformation gray scale bar graph g₂(x, y) often capable local fundamental component

S223, the local fundamental component by two width gray scale bar graphs per a line make local fundamental component along space x-axis respectively Superposition, obtains original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y) per a line₁(x, y_k) With f₂(x, y_k)；

S224, the fundamental component f by two width gray scale bar graphs per a line₁(x, y_k) and f₂(x, y_k) folded along space y-axis respectively Plus, obtain original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two dimension of (x, y) Fundamental component f₂(x, y).

It is further used as preferred embodiment, step S3, which is specially：

Respectively to original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂(x, Y) two-dimentional fundamental component f₂(x, y) does inverse Fourier transform, obtains fundamental frequency complex signal C of two width gray scale bar graphs₁With C₂, so Afterwards respectively to fundamental frequency complex signal C₁With C₂Phase angle is taken, original gradation bar graph g is obtained₁The wrapped phase of (x, y)With Deformation gray scale bar graph g₂The wrapped phase of (x, y)The wrapped phaseAnd wrapped phase Mathematical expression be expressed as：

Wherein, Im [] represents the imaginary part for taking complex signal, and Re [] represents the real part for taking complex signal.

Embodiment one

The three-dimension digital imaging device that the present embodiment pair is matched with the method for the present invention is illustrated.

The three-dimension digital imaging device matched with the method for the present invention, mainly includes digital projection illumination emitters, figure As sensing receiver and image processor.Wherein, digital projection illumination emitters can be that (LCD throws digital lcd projection arrangement Shadow instrument), digital micro mirror projection device (DMD projecting apparatus) or silicon chip liquid crystal projection apparatus (LCOS projecting apparatus), computer can be used Image processing system is conveniently generated gray scale candy strip and writes digital projection device.Image sensing receiver includes that light is studied As lens and photodetector, optical imaging lens can be focus away from or varifocal imaging len or lens group, binary optical Learn imaging system, diffraction element imaging system or micro imaging system.And photoelectric detector can be charge-coupled image sensor, liquid Brilliant device, spatial light modulation device, cmos device or digital camera.Image processor is that digital signal processor is special with programmable With the combination of integrated circuit, or the combination of general image process card and computer.

With reference to Fig. 6, the emergent pupil I of the projection lens 102 of digital projection transmitter 101, the imaging of image sensing receiver 103 are saturating In the center O of the entrance pupil P and illuminated field of mirror 104 is generally aligned in the same plane, and the emergent pupil I of projection lens 102 and imaging len 104 Entrance pupil P generally within same level height, so as to form a triangulation system.By image processor 105 computer or The sinusoidal gray scale bar graph Jing digital projections transmitter 101 that digital signal processor is produced is incident upon 106 He of article carrying platform respectively The surface of object 107,103 priority of image sensing receiver receive initial sinusoids gray scale bar graph on article carrying platform 106 and By the deformation gray scale bar graph of 107 depth modulation of object, it is sent to image processor 105 and is processed.Image processor 105 passes through Phasing matrix is extracted from two width gray scale bar graphs and difference operation is done, and the system obtained with reference to uncalibrated image sensor is joined Number, obtains the complete 3-dimensional digital picture of object.

Embodiment two

The present embodiment enters to a series of S-transformation matrixes that each enforcement generalized S-transform of gray scale bar graph of the present invention is obtained The process of row energy intensity optimization is illustrated.

The present invention energy intensity optimization process be：

To original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) per a lineWith" ridge " carry out the setting of energy intensity threshold value, it is excellent to carry out energy intensity to S-transformation matrix Change, it is ensured that when carrying out finding optimal S-transformation matrix based on encircled energy principle, its energy intensity is sufficient for 3-dimensional digital Imaging.One unified energy intensity threshold value E is set, as certain S-transformation matrix S_pThe minimum of energy intensity on " ridge " of (b, f) When the ratio of the maximum of energy intensity is less than E in value and " ridge ", this S-transformation matrix S is rejected_p(b, f), remaining preferred S become Change matrix and should meet following condition：

Wherein, (b_ii, f_ii)∈Ω(b_ii,f_ii), then after energy intensity optimization, original gradation bar graph g₁(x, y) with Deformation gray scale bar graph g₂A series of (x, y) each S-transformation matrix for being about to obtain Jing energy intensities optimizationsWith

Experiments verify that, when energy intensity threshold value takes 0.8 or so, effect is more satisfactory.

Embodiment three

The present embodiment is to piecing together out optimal S-transformation matrix of the gray scale bar graph per a line using generalized S-transform in the present invention When the encircled energy principle that adopted illustrate.

The process pieced together by the encircled energy principle that adopts of the present invention for：

First, each S-transformation square in a series of S-transformation matrixes of energy intensity optimization of passing through each to gray scale bar graph Battle array S_p(b, f) Frequency point f one by one_jjCalculating corresponds to the encircled energy of that a line.Certain S-transformation matrix S_p(b, f) is in a certain frequency Rate point f_jjThe encircled energy for locating that row is defined as：

Wherein, q is a constant.Experiments verify that, when q takes 0.2 or so, effect is more satisfactory.

Then, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of Jing energy of (x, y) per a line The S-transformation matrix of amount strength optimizationWithFrequency point f one by one_jjComparison corresponds to the energy of that a line Concentration degree CM (f_jj, p), select a certain Frequency point f_jjThat row of the maximum S-transformation matrix of place's encircled energy is used as piecing together out Optimal S-transformation matrix correspondence that a lineEnable the optimal S-transformation matrix pieced together out more smart Local fundamental component is positioned accurately.

It is more than that the preferable enforcement to the present invention is illustrated, but the invention is not limited to the enforcement Example, those of ordinary skill in the art on the premise of without prejudice to spirit of the invention can also be made a variety of equivalent variations or be replaced Change, the deformation or replacement of these equivalents are all contained in the application claim limited range.

Claims (6)

1. the three-dimension digital imaging method based on generalized S-transform, it is characterised in that：Including：

S1, coding is carried out to structure light generate sinusoidal gray scale bar graph, and sinusoidal gray scale bar graph is projected by projector equipment In reference planes, the original gradation bar graph g in monoscopic is obtained by video camera₁Then the object to be imaged is placed by (x, y) In reference planes, the deformation gray scale bar graph g in monoscopic by object depth information modulation is obtained by video camera₂(x, y)；

S2, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂(x, y) carries out strong based on energy Degree optimization and the generalized S-transform of encircled energy principle, and original gradation bar graph g is calculated by filtering method₁(x's, y) Fundamental component f₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y)₂(x, y)；

S3, fundamental component f respectively to extracting from two width gray scale bar graphs₁(x, y) and f₂(x, y) carries out Fourier's inversion Change, phase angle is taken to the result of inverse Fourier transform respectively then, obtain original gradation bar graph g₁The wrapped phase of (x, y)With deformation gray scale bar graph g₂The wrapped phase of (x, y)

S4, to wrapped phaseWithPhase unwrapping is carried out respectively obtains continuous phase distributionWithAnd the phase difference comprising object depth modulation information is obtained according to the result of phase unwrappingThe phase differenceComputing formula be：

S5, the camera parameters and Object Depth and phase of according to Fourier Transform Profilomery measuring principle, demarcating monocular imaging system The mapping relations of position change, and according to the phase difference for obtainingThe three-dimensional coordinate of the object to be imaged per is calculated, so as to reality The 3 D digital imaging of the existing object to be imaged；

Step S2, which includes：

S21, original gradation bar graph g respectively to obtaining₁(x, y) and deformation gray scale bar graph g₂Each row of (x, y) carries out base In energy intensity optimization and the generalized S-transform of encircled energy principle, original gradation bar graph g is obtained₁(x, y) and deformation gray scale Bar graph g₂The optimal S-transformation matrix of (x, y) per a line, the definition of the generalized S-transform is：

$\begin{array}{c}{S}_p(b,f){|}_{y=y_k}=\underset{-\mathrm{\∞}}{\overset{\mathrm{\∞}}{\∫}}g(x,y_k)w(b-x,\mathrm{\σ}(f\left)\right)\exp (-j2\mathrm{\π}fx)dx\\ =\underset{-\mathrm{\∞}}{\overset{\mathrm{\∞}}{\∫}}g(x,y_k)\frac{|f{|}^p}{\sqrt{2\mathrm{\π}}}\exp \left(\frac{{(b-x)}^2{f}^{2p}}{2}\right)\exp (-j2\mathrm{\π}fx)dx\end{array},$

Wherein, f is frequency, y_k=1,2 ..., y_max,g(x,y_k) represent gray scale bar graph row k, w (b-x, σ (f)) table Show be centrally located at x=b and standard deviation for σ (f) Gauss function, σ (f)=1/ | f |^p, p is constant；

S22, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation square of (x, y) per a line Battle array carries out the filtering based on local spectrum, obtains original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, y) is each Capable fundamental component, then the every a line fundamental component for obtaining is overlapped in the y-direction, so as to obtain original gradation bar graph g₁ The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two-dimentional fundamental component f of (x, y)₂(x, y).

2. the three-dimension digital imaging method based on generalized S-transform according to claim 1, it is characterised in that：The step S21, which includes：

S211, the initial value p to parameter p of Gauss function in generalized S-transform₀, iteration interval Δ p and iteration final value p_tSet Put；

S212, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂Every a line application broad sense S of (x, y) becomes Change, so as to obtain every a line g of original gradation bar graph₁(x,y_k) with deformation gray scale bar graph every a line g₂(x,y_k) in ginseng Number p takes a series of S-transformation matrixes during different valueWithThe S-transformation matrixWithExpression formula be：

$\left\{\begin{array}{c}{S}_1{|}_{y=y_k}=\left\{S_{p_0},S_{p_0+\mathrm{\Δ}p},\mathrm{......},S_{\frac{p_t-p_0}{\mathrm{\Δ}p}+1}|y=y_k\right\}\\ S_2{|}_{y=y_k}=\left\{{S^{\′}}_{p_0},{S^{\′}}_{p_0+\mathrm{\Δ}p},\mathrm{......},{S^{\′}}_{\frac{p_t-p_0}{\mathrm{\Δ}p}+1}|y=y_k\right\}\end{array}\right.;$

S213, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) per a lineWithMatrix " ridge " is found respectively：If a certain S-transformation matrix S_pThe energy of (b, f) at point (b, f) place is strong Spend the absolute value for its amplitude | S_p(b, f) |, then for each spatial point b_ii, b_ii=1,2 ... ..., b_max, its energy intensity Will be corresponding to S during acquirement maximum_pA maximum of points in (b, f) is to (b_ii, f_ii), and all maximums in all spatial points Point to set constitute S-transformation matrix S_p" ridge " Ω (b of (b, f)_ii,f_ii)；

S214, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) per a lineWith" ridge " carry out the setting of energy intensity threshold value, and S is become according to the energy intensity threshold value for arranging Changing matrix carries out energy intensity optimization, so as to obtain original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, y) is every One pass through energy intensity optimization a series of S-transformation matrixesWith

Each S-transformation matrix S in S215, a series of S-transformation matrixes of energy intensity optimization of passing through each to gray scale bar graph_p (b, f), one by one Frequency point f_jjCalculate Frequency point f_jjEncircled energy CM (the f of correspondence row_jj, p), the encircled energy CM (f_jj, expression formula p) is：

$CM(f_{jj},p)=\frac{1}{{\∫}_{-\mathrm{\∞}}^{\mathrm{\∞}}|S_p(b,f){|}^{q}db},$

Wherein, q is constant, f_jj=1,2 ... ..., f_max；

S216, to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, y) each energy intensity optimization of passing through A series of S-transformation matrixesWithThe optimal S-transformation of this line is pieced together out using encircled energy principle MatrixWith

3. the three-dimension digital imaging method based on generalized S-transform according to claim 2, it is characterised in that：The step S214, which is specially：

One unified energy intensity threshold value E is set, is appointed in then judging a series of S-transformation matrixes of the gray scale bar graph per a line One S-transformation matrix S_pOn " ridge " of (b, f), whether energy intensity minimum of a value is little with the ratio of energy intensity maximum on " ridge " In E, this S-transformation matrix S is if so, then rejected_p(b, f), conversely, then retain, so as to obtain original gradation bar graph g₁(x, y) with Deformation gray scale bar graph g₂A series of S-transformation matrixes of (x, y) each energy intensity optimization of passing throughWith

4. the three-dimension digital imaging method based on generalized S-transform according to claim 2, it is characterised in that：The step S216, which is specially：

A series of S-transformation matrix of the Jing energy intensities optimizations to gray scale bar graph per a lineFrequency point f one by one_jj Comparison corresponds to the encircled energy CM (f of that a line_jj, p), the S-transformation matrix of maximum that row of encircled energy is selected as correspondence The optimal S-transformation matrix that a line pieces together outThe optimal S-transformation matrixMeet：

$\left\{\begin{array}{c}CM(f_{jj},p_{opt})=|CM(f_{jj},p){|}_{\max }\\ S(b,f_{jj}){|}_{y=y_k}=S_{p_{opt}}(b,f_{jj}){|}_{y=y_k}\\ S_{opt}(b,f){|}_{y=y_k}=\underset{f_{jj}=1}{\overset{f_{\max }}{\Σ}}S(b,f_{jj}){|}_{y=y_k}\end{array}\right.,$

Wherein, p_optRefer to the optimum p value of that a line of encircled energy maximum correspondence.

5. the three-dimension digital imaging method based on generalized S-transform according to claim 1, it is characterised in that：The step S22, which includes：

S221, according to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The optimal S-transformation matrix of (x, y) per a line Local fundamental component is accurately positioned；

S222, according to default filtering window function, respectively to original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂(x, Y) the optimal S-transformation matrix per a line carries out the filtering based on local spectrum, obtains original gradation bar graph g₁(x, y) often goes Local fundamental componentAnd deformation gray scale bar graph g₂(x, y) often capable local fundamental component

S223, the local fundamental component by two width gray scale bar graphs per a line make local fundamental component superposition along space x-axis respectively, Obtain original gradation bar graph g₁(x, y) and deformation gray scale bar graph g₂The fundamental component f of (x, y) per a line₁(x, y_k) and f₂(x, y_k)；

S224, the fundamental component f by two width gray scale bar graphs per a line₁(x, y_k) and f₂(x, y_k) be superimposed along space y-axis respectively, obtain To original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂The two-dimentional fundamental frequency of (x, y) Component f₂(x, y).

6. the three-dimension digital imaging method based on generalized S-transform according to claim 5, it is characterised in that：The step S3, which is specially：

Respectively to original gradation bar graph g₁The two-dimentional fundamental component f of (x, y)₁(x, y) and deformation gray scale bar graph g₂(x's, y) Two-dimentional fundamental component f₂(x, y) does inverse Fourier transform, obtains fundamental frequency complex signal C of two width gray scale bar graphs₁With C₂, Ran Houfen It is other to fundamental frequency complex signal C₁With C₂Phase angle is taken, original gradation bar graph g is obtained₁The wrapped phase of (x, y)And deformation Gray scale bar graph g₂The wrapped phase of (x, y)The wrapped phaseAnd wrapped phaseNumber Formula is expressed as：

Wherein, Im [] represents the imaginary part for taking complex signal, and Re [] represents the real part for taking complex signal.