CN107680066A - Space camera dynamic imaging emulates and frequency domain filtering method - Google Patents
Space camera dynamic imaging emulates and frequency domain filtering method Download PDFInfo
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Abstract
The present invention relates to the emulation of space camera dynamic imaging and frequency domain filtering method, this method carries out dynamic modeling for the exposure image of space camera imaging system, simulate system dynamic point receptance function movement locus and imaging effect under different exposure time, the method that the relevant information of adjacent exposure is passed through into norm optimization simultaneously, obtain apparent image, by being lifted as matter, increase the perception to dark weak signal target and pre-alerting ability, there is important value；This method can be used for lifting early warning class image slices matter, strengthens the perception to dark weak signal target, realizes early warning；Solve that existing onboard processing method is not accurate enough to in-orbit dynamic imaging characteristic present, the problem of causing to be difficult to resolve dark Weak target information using ground static point receptance function.
Description
Technical field
The present invention relates to a kind of space camera dynamic imaging emulation and frequency domain filtering method, belong to optical data emulation with
Processing technology field.
Background technology
Space camera is in-orbit to be influenceed by various extraneous factors, such as camera directing mechanism precision mismatch, camera posture
Drift, the impact of launching phase causes optical component relative space position to change, the in-orbit temperature difference is relatively large causes phase
Thermal deformation etc. occurs for machine position of focal plane.In addition, in-orbit camera easily causes noise under cosmic ray, it is especially in-orbit
System dynamic characteristic changes in multiple exposure process, causes each imageable target detection dynamic point receptance function change, and then
Image quality is had a strong impact on, is ultimately resulted in as matter blur degradation.In-orbit target dynamic point receptance function and the static state of ground survey
Point receptance function is not inconsistent, while produces a large amount of not expected noises.
At present, a receptance function is obtained as systematic parameter according to ground survey typically in engineering.Because this mesh
Scalar functions characterize the detection feature of static system, are but difficult to characterize system dynamic characteristic, therefore be used as system response function by the use of it
It is difficult to be finally inversed by position and the strength information of target, the inverting and interpretation of in-orbit data are influenceed, so that influenceing early warning.
The content of the invention
It is an object of the invention to overcome the drawbacks described above of prior art, there is provided a kind of space camera dynamic imaging emulation
And frequency domain filtering method, this method breaks through the bottleneck that tradition relies on the test of ground static function, for in-orbit estimation dynamic response
Data carry out information processing, obtain apparent image, and this method can effectively room for promotion camera be in-orbit is imaged as matter, adds
By force to the perception of target, early warning is realized.
What the above-mentioned purpose of the present invention was mainly achieved by following technical solution：
Space camera dynamic imaging emulates and frequency domain filtering method, specifically comprises the following steps：
Step (1), each exposure image founding mathematical models to space camera, wherein to ith exposure image LiBuild
Vertical mathematical modeling QiIt is as follows：
Wherein：prfIt is dynamic, iFor the space camera system dynamic point receptance function of ith exposure, IIt is preferableFor ideal image, n is
The system noise of space camera；
Step (2), the mathematical modeling to each exposure image of space camera carry out Fourier transformation, wherein being exposed to ith
Light image LiMathematical modeling QiFourier transformation is carried out, the spectrum information after being converted is Fi(μ,ν)；
Step (3), the spectrum information F to adjacent double exposure imagei(μ, ν) and Fi-1(μ, ν) carries out norm optimization about
Beam, obtain the spectrum information F after norm optimization constraintEventually(μ,ν)；
Step (4), to norm optimization constrain after spectrum information FEventually(μ, ν) does inverse Fourier transform, obtains image LEventually
(μ,ν)。
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, described hollow camera system of step (1)
Dynamic point receptance function prfIt is dynamic, iRepresent as follows：
Wherein：H (x, y) is static system point receptance function, RiFor system dynamic point receptance function integral function；
Wherein：(x0,y0) it is target projection center position coordinates, (x, y) is target projection position coordinates；
C is the distribution of target energy, and σ is the standard deviation of Gauss point receptance function distribution.
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, the system dynamic point receptance function product
Divide function RiExpression formula it is as follows：
Wherein：TiFor the ith time for exposure；δk(t)For delta function；T is imaging time.
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, to being exposed to ith in the step (2)
Light image LiMathematical modeling Q carry out Fourier transformation, the spectrum information F after being convertedi(μ, ν) specifically represents as follows：
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, exposed twice to adjacent in the step (3)
The spectrum information F of light imagei(μ, ν) and Fi-1(μ, ν) carries out norm optimization constraint, obtains the frequency spectrum letter after norm optimization constraint
Cease FEventuallyThe specific method of (μ, ν) is as follows：
As k=n-1, obtained FEventually, k+1(μ, ν) is final spectrum information FEventually(μ,ν)；
Wherein：τiFor gradient terms constraint factor；βiFor the degree of correlation between spectrum information after adjacent exposure, Ω is frequency spectrum branch
Support domain；Fi,k(μ, ν) is the spectrum information that ith exposes in kth time iteration；Fi-1,k(μ, ν) is the i-th -1 time in kth time iteration
The spectrum information of exposure；PRFi(μ, ν) is the Fourier transformation of the system dynamic point receptance function of space camera；N is iteration time
Number；FEventually, k(μ, ν) is the spectrum information F after the norm optimization constraint that kth time iteration obtainsEventually(μ, ν), FEventually, k+1(μ, ν) is kth
Spectrum information F after the norm optimization constraint that+1 iteration obtainsEventually(μ,ν)；
TVi,ΩExpression image gradient information, expression are as follows：
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, the gradient terms constraint factor τiMeet τi
∈[0,1]；Degree of correlation β after the adjacent exposure between informationiMeet βi∈[0,1]。
In the emulation of above-mentioned space camera dynamic imaging and frequency domain filtering method, the step (4) is to spectrum information FEventually
(μ, ν) does inverse Fourier transform, obtains image LEventually(μ, ν), expression is as follows：
LEventually(x, y)=IFFT (FEventually(μ, v)).
The present invention has the advantages that compared with prior art：
(1), the present invention carries out dynamic modeling for the exposure image of space camera imaging system, when simulating different exposures
Between lower system dynamic point receptance function movement locus and imaging effect, while the relevant information of adjacent exposure is passed through into norm
The method of optimization, apparent image is obtained, by being lifted as matter, increases the perception to dark weak signal target and early warning ability,
With important military value；This method can be used for lifting early warning class image slices matter, strengthen the perception energy to dark weak signal target
Power, realize early warning；
(2), the present invention is directed to the in-orbit information processing of space camera and increased quality method, and in-orbit dynamic is carried out to target
Imaging modeling, while data are merged and rebuild using the system response message of adjacent imaging, the present invention breaks through tradition
The bottleneck of ground static function test is relied on, information processing is carried out for in-orbit estimation dynamic response data, obtains apparent
Image, this method can effectively room for promotion camera it is in-orbit imaging as matter, solve existing onboard processing method to in-orbit
Dynamic imaging characteristic present is not accurate enough, causes to be difficult to resolve asking for Small object information using ground static point receptance function
Topic.
(3), space camera dynamic imaging emulation of the present invention and frequency domain filtering method, are used to the spectrum information of adjacent time
The L of particular designpNorm optimization constraint is handled, and more effective detail of the high frequency can be obtained, so as to obtain more
Clearly high fidelity visual, lift picture quality.
Brief description of the drawings
Fig. 1 is space camera dynamic imaging of the present invention emulation and frequency domain filtering method flow diagram；
Fig. 2 is hollow camera system static point receptance function figure of the embodiment of the present invention, and wherein Fig. 2 a are two-dimensional signal,
Fig. 2 b are three-dimensional information.
Fig. 3 is system dynamic point receptance function track and degraded image simulation drawing in the embodiment of the present invention；
Fig. 4 is to use adjacent secondary exposure information restored image result in the embodiment of the present invention.
Embodiment
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings：
To be for space camera dynamic imaging of the present invention emulation and frequency domain filtering method flow diagram, the present invention as shown in Figure 1
Imaging process of uniting influences system dynamic point receptance function and considered in model, and in-orbit imaging system point receptance function is degenerated, and point rings
Answer function to change over time, show as target point in the picture and be subjected to displacement, the present invention emulates to a receptance function, simulates point
Receptance function is moved by platform to be changed and caused change into the projection on two axial directions, causes imaging session is different to expose
The trail change of point receptance function under between light time, while simulate system noise under different exposure time.Finally, utilization is adjacent
The prior information of relevant information and system after secondary exposure removes influence of the in-orbit imaging dynamic factor of system to imaging, finally
Clearly target image information is recovered, is specifically comprised the following steps：
First, the mathematical modeling of exposure image is established
Space camera imaging system be can be considered into linear system, set LiFor the ith exposure image of acquisition；Test is empty
Between the point receptance function of camera under various environmental conditions, determine the various prior informations of camera and in-orbit state estimations.Setting
prfIt is dynamic, iFor the space camera system dynamic point receptance function of ith exposure；IIt is preferableFor ideal image；N is system noise.IfWherein h is static system point receptance function, RiFor system dynamic point receptance function integral function.
Ith exposure image L of the present invention to space cameraiWith the i-th -1 time exposure image Li-1Mathematical modulo is established respectively
Type QiWith Qi-1It is as follows：
Wherein：prfIt is dynamic, i、prfIt is dynamic, i-1Respectively ith, the space camera system dynamic point response letter of the i-th -1 time exposure
Number, IIt is preferableFor ideal image, n is the system noise of space camera.
Space camera system dynamic point receptance function prfIt is dynamic, iRepresent as follows：
Wherein：H (x, y) is static system point receptance function, RiFor the time integral letter of system dynamic point receptance function
Number；
Wherein：(x0,y0) it is target projection center position coordinates, (x, y) is target projection position coordinates；C is PSF circle
The distribution of shape support region, i.e. target energy, σ are the standard deviation of Gauss point receptance function distribution, reflect target energy point
The scope of diffusion effect, receptance function radius or dilation angle are also referred to as put, σ takes 0.001 in the present embodiment.
Wherein：TiFor the ith time for exposure；δk(t)For delta function；T is imaging time.
If exposure frequency is n times, each time for exposure is identical, then Ti=t/n.In Fu of system dynamic point receptance function
Leaf transformation is PRFi。
2nd, Fourier transformation is carried out to the mathematical modeling of each exposure image of space camera, to ith exposure image Li
Mathematical modeling and the i-th -1 time exposure image Li-1Mathematical modeling carry out Fourier transformation respectively, the frequency spectrum after being converted
Information Fi(μ,ν) and Fi-1(μ,ν)；
Further spread out to obtain：
Wherein：M, N are the size of image, and μ, ν are positional information in frequency domain information；(x, y) sits for target projection position
Mark.
3rd, to the spectrum information F of adjacent double exposure imagei(μ, ν) and Fi-1(μ, ν) carries out norm optimization constraint, obtains
Spectrum information F after being constrained to norm optimizationEventuallyThe specific method of (μ, ν) is as follows：
Obtain the spectrum information F after norm optimization constraintEventuallyThe process of (μ, ν) is the process of an iteration, works as k=n-1
When, obtained FEventually, k+1(μ, ν) is final spectrum information FEventually(μ,ν)。
Wherein：τiFor gradient terms constraint factor；βiFor the degree of correlation between spectrum information after adjacent exposure, Ω is frequency spectrum branch
Support domain；Fi,k(μ, ν) is the spectrum information that ith exposes in kth time iteration；Fi-1,k(μ, ν) is the i-th -1 time in kth time iteration
The spectrum information of exposure；PRFi(μ, ν) is the Fourier transformation of the system dynamic point receptance function of space camera；μ, ν are frequency domain
Positional information in information；N is iterations. FEventually, k(μ, ν) is the frequency spectrum letter after the norm optimization constraint that kth time iteration obtains
Cease FEventually(μ, ν), FEventually, k+1(μ, ν) is the spectrum information F after the norm optimization constraint that+1 iteration of kth obtainsEventually(μ,ν)。
TVi,ΩExpression image gradient information, expression are as follows：
Wherein gradient terms constraint factor τiMeet τi∈[0,1]；Degree of correlation β after the adjacent exposure between informationiIt is full
Sufficient βi∈[0,1]。
The frequency domain information carried out first under norm space optimizes constraint, sets here2 norms are sought in expression
Minimize, p norm optimizations can be extended to, i.e.,Represent p norm minimums.Pass through alternative manner pair in the step
Frequency spectrum supporting domain Ω carries out frequency domain total variation constraint, obtains the frequency domain information F after final frequency domain total variation constraintEventually(μ, ν),
I.e. as k=n-1, obtained FEventually, k+1(μ, ν) is final spectrum information FEventually(μ,ν)。
4th, to spectrum information FEventually(μ, ν) does inverse Fourier transform, obtains image LEventually(μ,ν)。
LEventually(x, y)=IFFT (FEventually(μ, v))
Further spread out to obtain equation below：
Embodiment 1
The selection for testing spectral coverage is determined according to infrared radiation characteristics, and selection target is experimental image.Experimental result can
See, the image after rebuilding after filtering is apparent, effectively removes the image caused by system dynamic imaging etc. and obscures, lifts picture
Matter.
If table 1 below is that the quality evaluation result of image procossing is carried out using the inventive method and several conventional methods.
The picture quality objective evaluation result of table 1
Illustrated by the quantitative indices of table 1, compared with conventional method, the inventive method is kept at comentropy, variance, edge
The indexs such as degree, signal noise ratio (snr) of image improve than conventional method.Can effectively it remove caused by the factors such as systematic error after treatment
Image obscures, and is advantageous to subsequently sentence figure and target identification.
Hollow camera system static point receptance function figure of the embodiment of the present invention is illustrated in figure 2, wherein Fig. 2 a are two dimension
Information, Fig. 2 b are three-dimensional information.System describes dynamic characteristic such as Fig. 3 of target and imaging system using dynamic point receptance function
Shown, Fig. 3 is system dynamic point receptance function track and degraded image simulation drawing in the embodiment of the present invention；Then system is utilized
Prior information related and norm minimum carried out to the relevant information after adjacent time exposure constrained, carry out interframe Federated filter
Method.The image finally rebuild after synthetic filtering is as shown in figure 4, Fig. 4 is using adjacent exposure letter in the embodiment of the present invention
Cease restored image result.From fig. 4, it can be seen that the image after rebuilding after filtering is apparent, effectively remove because of system dynamic imaging etc.
Caused by image obscure, lifted as matter.
It is described above, it is only an embodiment of the invention, but protection scope of the present invention is not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can readily occur in,
It should all be included within the scope of the present invention.
Unspecified part of the present invention belongs to general knowledge as well known to those skilled in the art.
Claims (7)
1. space camera dynamic imaging emulates and frequency domain filtering method, it is characterised in that：Specifically comprise the following steps：
Step (1), each exposure image founding mathematical models to space camera, wherein to ith exposure image LiThe number of foundation
Learn model QiIt is as follows：
Wherein：prfIt is dynamic, iFor the space camera system dynamic point receptance function of ith exposure, IIt is preferableFor ideal image, n is space phase
The system noise of machine；
Step (2), the mathematical modeling to each exposure image of space camera carry out Fourier transformation, wherein to ith exposure diagram
As LiMathematical modeling QiFourier transformation is carried out, the spectrum information after being converted is Fi(μ,ν)；
Step (3), the spectrum information F to adjacent double exposure imagei(μ, ν) and Fi-1(μ, ν) carries out norm optimization constraint, obtains
Spectrum information F after norm optimization constraintEventually(μ,ν)；
Step (4), to norm optimization constrain after spectrum information FEventually(μ, ν) does inverse Fourier transform, obtains image LEventually(μ,ν)。
2. space camera dynamic imaging emulation according to claim 1 and frequency domain filtering method, it is characterised in that：The step
Suddenly (1) hollow camera system dynamic point receptance function prfIt is dynamic, iRepresent as follows：
Wherein：H (x, y) is static system point receptance function, RiFor system dynamic point receptance function integral function；
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Wherein：(x0,y0) it is target projection center position coordinates, (x, y) is target projection position coordinates；C is point of target energy
Cloth scope, σ are the standard deviation of Gauss point receptance function distribution.
3. space camera dynamic imaging emulation according to claim 2 and frequency domain filtering method, it is characterised in that：The system
Unite dynamic point receptance function integral function RiExpression formula it is as follows：
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Wherein：TiFor the ith time for exposure；δk(t)For delta function；T is imaging time.
4. space camera dynamic imaging emulation according to claim 1 and frequency domain filtering method, it is characterised in that：The step
Suddenly to ith exposure image L in (2)iMathematical modeling Q carry out Fourier transformation, the spectrum information F after being convertedi(μ,
It is ν) specific to represent as follows：
5. space camera dynamic imaging emulation according to claim 1 and frequency domain filtering method, it is characterised in that：The step
Suddenly to the spectrum information F of adjacent double exposure image in (3)i(μ, ν) and Fi-1(μ, ν) carries out norm optimization constraint, obtains norm
Spectrum information F after optimization constraintEventuallyThe specific method of (μ, ν) is as follows：
As k=n-1, obtained FEventually, k+1(μ, ν) is final spectrum information FEventually(μ,ν)；
Wherein：τiFor gradient terms constraint factor；βiFor the degree of correlation between spectrum information after adjacent exposure, Ω is frequency spectrum supporting domain；
Fi,k(μ, ν) is the spectrum information that ith exposes in kth time iteration；Fi-1,k(μ, ν) is the i-th -1 time exposure in kth time iteration
Spectrum information；PRFi(μ, ν) is the Fourier transformation of the system dynamic point receptance function of space camera；N is iterations；FEventually, k
(μ, ν) is the spectrum information F after the norm optimization constraint that kth time iteration obtainsEventually(μ, ν), FEventually, k+1(μ, ν) is+1 iteration of kth
Spectrum information F after obtained norm optimization constraintEventually(μ,ν)；
TVi,ΩExpression image gradient information, expression are as follows：
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<mn>2</mn>
</msup>
</mrow>
</msqrt>
<mo>.</mo>
</mrow>
6. space camera dynamic imaging emulation according to claim 5 and frequency domain filtering method, it is characterised in that：The ladder
Spend item constraint coefficient τiMeet τi∈[0,1]；Degree of correlation β after the adjacent exposure between informationiMeet βi∈[0,1]。
7. space camera dynamic imaging emulation according to claim 1 and frequency domain filtering method, it is characterised in that：The step
Suddenly (4) are to spectrum information FEventually(μ, ν) does inverse Fourier transform, obtains image LEventually(μ, ν), expression is as follows：
LEventually(x, y)=IFFT (FEventually(μ, v)).
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