CN109345481A - A kind of quantum optimization method for aerospace optical remote sensing image - Google Patents
A kind of quantum optimization method for aerospace optical remote sensing image Download PDFInfo
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Abstract
The present invention provides a kind of quantum optimization methods for aerospace optical remote sensing image: (1), satellite pass by and be imaged over the ground, obtain the remote sensing image of observed object, and be normalized；(2), normalized remote sensing image is transformed into vector subspace, decomposed on n quantum bit face, obtain quantum state vector of the remote sensing image quantization information on each quantum bit face；(3), quantum state vector of the remote sensing image quantization information on each quantum bit face is filtered using the method for norm optimization based on optical remote sensing imaging system models；(4), the quantum state vector by filtered remote sensing image quantization information on each quantum bit face, carries out enhancing processing, obtains the quantum state vector on each quantum bit face of enhancingization；(5), the quantum state vector reconstruction on each quantum bit face of enhancingization is converted into high-resolution remote sensing image.The present invention can effectively improve evaluation index.
Description
Technical field
The present invention provides a kind of remote sensing image quantization filtering methods, belong to optical remote sensing information processing technology neck
Domain.
Background technique
The in-orbit imaging session of optical sensor at present causes ground resolution very low since detector size is limited, and because
The Various Complexes factors such as space environment variation cause detection component performance degradation a large amount of random noises, such as photon occur in focal plane
Noise, thermal noise etc. lead to occur in acquired image speckle noise and system ambiguous；Along with sensitive detection parts are inherently special
Property, down-sampling is implemented to the continuous natural feature on a map signal of signal and causes image integral energy insufficient, image quality is seriously degenerated.
Currently, the satellite in-orbit stage, since its processing capacity is limited, it is difficult to effectively promotion image quality, using traditional equal
Value filtering loses a large amount of effective information while denoising, it is difficult to obtain ideal effect, noise estimation is not accurate enough.Therefore, it needs
To use the further improving optical sensor image quality of new tool.
Summary of the invention
Technology of the invention solves the problems, such as: overcoming the deficiencies of the prior art and provide a kind of remote sensing image quantization
Filtering method, improving optical sensor image quality.
The technical solution of the invention is as follows: a kind of quantum optimization method for aerospace optical remote sensing image, this method
Include the following steps:
(1), satellite passes by and is imaged over the ground, using optical remote sensing imaging system, obtains the remote sensing image of observed object,
And it is normalized；
(2), normalized remote sensing image is transformed into vector subspace, decomposes on n quantum bit face, obtains light
Learn quantum state vector of the remote sensing images quantization information on each quantum bit face；
(3), optical remote sensing imaging system models are based on, using the method for norm optimization, by remote sensing image quantization
Quantum state vector of the information on each quantum bit face is filtered；
(4), the quantum state vector by filtered remote sensing image quantization information on each quantum bit face carries out
Enhancing processing, obtains the quantum state vector on each quantum bit face of enhancingization；
(5), the quantum state vector reconstruction on each quantum bit face of enhancingization is converted into high-resolution optical remote sensing figure
Picture.
Quantum state vector of the remote sensing image quantization information on each quantum bit face is expressed as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n]
In formula, pkThe corresponding quantization information of remote sensing image is represented in the probability amplitude in k-th of quantum bit face, | ψk
(μ, ν)>be the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face right arrow,<ψk
(μ, ν) | be the bra vector of the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face, be | ψk
(μ, ν) > conjugate transposition, (μ, ν) represents position coordinates of the quantum state vector on quantum bit face.
The right arrow of the corresponding quantization information of described image quantum state vector in k-th of quantum bit face | ψk(μ,ν)>
Expression formula are as follows:
In formula, | 0 > and | 1 > two ground state in image quantum bit are expressed as, f is the optical remote sensing after normalization
Image, f (m, n) ∈ [0,1].
In the case that image pixel value is according to exponential distribution probability distribution, the corresponding quantization information of described image is
The right arrow of quantum state vector in k quantum bit face | ψk(μ, ν) > expression formula are as follows:
In formula, θ and φ respectively indicate quantum bit and spatially correspond to vector and cartesian product coordinate system z-axis angle；It is corresponding
Angle of the vector projection between the cartesian product face coordinate system XOY and X-axis.
The step (2) uses " 2+p " norm optimization method, by remote sensing image quantization information in each quantum bit
Quantum state vector on face is filtered.
" 2+p " the norm optimization method are as follows: seek perfect optics remote sensing images I in k-th of quantum bit face quantum state
The right arrow of vectorIt is allowed to meet following formula:
To by perfect optics remote sensing images I k-th of quantum bit face quantum state vector right arrowMake
It is filtered remote sensing image I in the right arrow of k-th of quantum bit face quantum state vector, calculates again later
Conjugate transposition, obtain filtered remote sensing image I in the bra vector of k-th of quantum bit face quantum state vector；
In formula,It is the corresponding matrix H of optical remote sensing imaging system point spread function in k-th of quantum bit
The right arrow of face quantum state vector；
The normalized remote sensing image got for step (1) is on k-th of quantum bit face
The right arrow of quantum state vector；
Indicate the quantum state vector on corresponding k-th of the quantum bit face optical remote sensing imaging system noise N
Right arrow；
λkFor the regulation coefficient of each bit-plane, take between 0~1 here；2 Norm minimums are sought in expression
Change, | | | |pIndicate p norm, 0 < p < 1, ρkFor Dynamic gene, 0 < ρk< 1, DkFor gradient value, and formula is as follows:
In formula, | Fk(μ, ν) > for the pixel at remote sensing image (μ, ν) corresponding quantum on k-th of bit-plane
Bit value.
The step (4) is enhanced image using bilateral filtering method.
Signal reconstruct method are as follows:
Wherein,It is the corresponding quantization information of enhanced remote sensing image in k-th of quantum bit
The right arrow of quantum state vector in face,It is the corresponding quantization information of enhanced remote sensing image at k-th
The bra vector of quantum state vector in quantum bit face isConjugate transposition；F'(m, n) be conversion after optics it is distant
Feel image.
Compared with the prior art, the invention has the advantages that:
(1), the present invention considers from quantum of information angle, it is contemplated that the information of superposition state simultaneously carries out model in quantum bit face
Number optimization, it is thus possible to which more effectively removal noise promotes the effective information of image.
(2), image information is transformed into vector subspace by the present invention, utilizes " 2+p norm " optimization characteristics by noise and signal
It is separated in vector subspace, information is then converted back into image information from vector subspace, obtain the image of quality enhancing, be suitable for
It can not be handled on star or ground is difficult to the image denoised.
(3), the method for the present invention has better details fidelity compared with traditional treatment method, can obtain clearer figure
Picture promotes image quality.
(4), the method for the present invention is filtered by vector subspace and is enhanced, can effective room for promotion camera in-orbit imaging image quality,
Reinforce the sensing capability to target.
(5), the present invention can be used for remote sensing image, be particularly suitable for infrared, Terahertz spectral coverage weak signal target, strong background is made an uproar
The removal of sound.
Detailed description of the invention
Fig. 1 is remote sensing image quantization filtering method flow chart of the present invention；
Fig. 2 is projection of the image of the embodiment of the present invention on each face Qbit；Wherein:
Fig. 2 (a)~Fig. 2 (h) is respectively the 1st layer~the 8th layer exploded view；
Fig. 3 the method for the present invention is compared with conventional process result；Wherein:
Fig. 3 (a) is that optical sensor of the present invention obtains image；
Fig. 3 (b) is the remote sensing image obtained using mean filter processing method；
Fig. 3 (c) is the remote sensing image obtained using processing method of the present invention (quantum filtering).
Specific embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.
The invention proposes one kind to be based on quantization image filtering method, and the present invention is examined from quantum of information state angle
Consider superposition state information, realizes denoising by filtering in vector subspace, then use enhancing filtering, what final lifting system obtained
Information content.Since information is expressed by way of quantum bit, it can be shown that the superposition state between information ground state, this
The noise for being present in superposition state is that traditional images processing method can not be handled, while use " the 2+P norm " in vector subspace
Preferably denoising effect is realized in optimization.Since this method realizes Advance data quality in vector subspace, noise separation effect is more preferable.
The method of the present invention overall procedure is as follows:
(1), satellite passes by and is imaged over the ground, using optical remote sensing imaging system, obtains the remote sensing image of observed object,
And it is normalized；
Specific implementation are as follows: satellite passes by and is imaged over the ground, and camera booting obtains Optical remote satellite and corresponds to target observation information；
In conjunction with optical remote sensing imaging system information, imaging system is modeled, remote sensing image is obtained.
(2), normalized remote sensing image is transformed into vector subspace, decomposes on n quantum bit face, obtains light
Learn quantum state vector of the remote sensing images quantization information on each quantum bit face；
The picture numerical value of remote sensing image is after normalization, and the gray value of each pixel is in [0,1] section.Optical remote sensing
Imaging system can be considered linear system, be expressed as follows:
In formula, (m, l) represents position coordinates of the pixel in remote sensing image.0 < m < M, 0 < l < L, to get figure
As the size of data, s is PSF size in one direction, and I (m, l) is ideal scenario information, and Noise is noise item, and H is represented
The point spread function (PSF) of optical remote sensing imaging system, can be obtained by measurement.There are two types of measurement methods, and it is logical that one is laboratories
Point source target is crossed, realizes the precise measurement to system point spread function (PSF).It is for second to be laid with ground in satellite substar of passing by
Face target realizes the measurement to satellite dynamic point spread function (PSF).In short, the point spread function (PSF) measured is with Two-Dimensional Moment
Battle array H-shaped formula expression, is expressed as s × s matrix of Gauss shape, conveniently takes for operation
Remote sensing image is transformed into vector subspace, decomposes on each quantum bit face, obtains remote sensing image
Quantum state vector in corresponding quantum bit face, can be expressed as follows:
Therefore, quantum state vector of the remote sensing image quantization information on each quantum bit face is expressed as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n] (3)
In formula, pkThe corresponding quantization information of remote sensing image is represented in the probability amplitude in k-th of quantum bit face, | ψk
(μ, ν)>be the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face right arrow,<ψk
(μ, ν) | be the bra vector of the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face, be | ψk
(μ, ν) > conjugate transposition, (μ, ν) represents position coordinates of the quantum state vector on quantum bit face.
The right arrow of the corresponding quantization information of described image quantum state vector in k-th of quantum bit face | ψk(μ,ν)>
Expression formula are as follows:
ψk(μ, ν) >=α | 0 >+β | 1 >
In formula, | 0 > and | 1 > two ground state in image quantum bit are expressed as, α, β respectively indicate ψk(μ, ν) >
| 0 > with | the probability in 1 > two ground state, α and β can be regarded as forming different polarization states after light is incident, and meet α2+β2=1.
F is the remote sensing image after normalization, f (m, n) ∈ [0,1].The corresponding quantization information of image can be existed
The right arrow of quantum state vector in k-th of quantum bit face | ψk(μ, ν) > expression formula are as follows:
In the case that image pixel value is according to exponential distribution probability distribution, can further it derive: described image pair
The right arrow of the quantization information answered quantum state vector in k-th of quantum bit face | ψk(μ, ν) > expression formula are as follows:
In formula, θ and φ respectively indicate quantum bit and spatially correspond to vector and cartesian product coordinate system z-axis angle；It is corresponding
Angle of the vector projection between the face xy and x-axis.In the embodiment of the present invention, remote sensing information can be analyzed to 8 bit-planes.
(3), optical remote sensing imaging system models are based on, using the method for norm optimization, by remote sensing image quantization
Quantum state vector of the information on each quantum bit face is filtered；
The embodiment of the present invention uses " 2+p " norm optimization method, by remote sensing image quantization information in each quantum ratio
Quantum state vector on special face is filtered, and filters out noise.
Specific filtering are as follows: seek perfect optics remote sensing images I on the right side of k-th of quantum bit face quantum state vector
ArrowIt is allowed to meet following formula:
To by perfect optics remote sensing images I k-th of quantum bit face quantum state vector right arrowMake
It is filtered remote sensing image I in the right arrow of k-th of quantum bit face quantum state vector, calculates again later
Conjugate transposition, obtain filtered remote sensing image I in the bra vector of k-th of quantum bit face quantum state vector；
In formula,It is the corresponding matrix H of optical remote sensing imaging system point spread function in k-th of quantum bit
The right arrow of face quantum state vector；
The normalized remote sensing image got for step (1) is on k-th of quantum bit face
The right arrow of quantum state vector；
Indicate the quantum state vector on corresponding k-th of the quantum bit face optical remote sensing imaging system noise N
Right arrow；
λkFor the regulation coefficient of each bit-plane, take between 0~1 here；2 Norm minimums are sought in expression
Change, | | | |pIndicate p norm, 0 < p < 1, ρkFor Dynamic gene, 0 < ρk< 1, DkFor gradient value, and formula is as follows:
In formula, | Fk(μ, ν) > for the pixel at remote sensing image (μ, ν) corresponding quantum on k-th of bit-plane
Bit value.
The norm space of quantum scope is similar to the norm space of image area, i.e., the norm table acquired in different bit-planes
Reach, expansion operation abide by quantum operation rule, by optimization so thatLevel off to ideal value.
For the corresponding matrix H of optical remote sensing imaging system PSF k-th of quantum bit face quantum state to
Amount；
It is perfect optics remote sensing images I in k-th of quantum bit face quantum state vector；
|ψk(μ0,ν0Quantum state vector of the remote sensing image that) > be gets on k-th of quantum bit face；
Indicate quantum state on corresponding k-th of the quantum bit face optical remote sensing imaging system noise N to
Amount.
The norm space of quantum scope is similar to the norm space of image area, i.e., the norm table acquired in different bit-planes
It reaches, quantum operation rule is abided by quantum vector operation:
Theorem: ifAndThen haveWithAnd have
With
The operation relation between any two quantum state vector is represented in above formula, wherein quantum state vector | ψj> matrix table
It is shown asAnd | ψp> matrix be expressed asTherefore, | ψj> with | ψp> between operation relation be all satisfied expansionWithBetween operation.Operation relation in this way between quantum state vector can be realized by operation between matrix.
(4), the quantum state vector by filtered remote sensing image quantization information on each quantum bit face carries out
Enhancing processing, obtains the quantum state vector on each quantum bit face of enhancingization；
There are many kinds of the methods of image enhancement, and the embodiment of the present invention is enhanced image using bilateral filtering method, real
It now keeps enhancing image texture information while marginal information, promote picture quality, filtered quantum information is
(5), the quantum state vector reconstruction on each quantum bit face of enhancingization is converted into high-resolution optical remote sensing figure
Picture.Specific signal reconstruct method are as follows:
Wherein,It is the corresponding quantization information of enhanced remote sensing image in k-th of quantum bit
The right arrow of quantum state vector in face,It is the corresponding quantization information of enhanced remote sensing image at k-th
The bra vector of quantum state vector in quantum bit face isConjugate transposition；F' is the optical remote sensing figure after conversion
Picture.
Embodiment:
Fig. 2 is image of the image after quantum bit face is decomposed, and as shown in Figure 2, quantum bit face of the present invention is decomposed can
It is finer to decompose the information in image, effectively noise and signal are separated.Fig. 3 is at the method for the present invention and conventional method
Reason result compares.Table 1 is to compare after traditional treatment method and quantization filter processing method of the present invention.
It is compared after 1 traditional treatment method of table and quantization filter processing method of the present invention
By 1 quantitative indices of table as it can be seen that being compared with the traditional method, this patent method is in signal noise ratio (snr) of image, contrast, information
The indexs such as entropy are higher.As seen from Figure 3, noise and fuzzy can be effectively removed after treatment, be conducive to subsequent sentence figure and target
Identification.
In conclusion being compared with the traditional method, the present invention is higher in indexs such as signal noise ratio (snr) of image, contrast, comentropies.
Noise and fuzzy can be effectively removed after treatment, be conducive to subsequent sentence figure and target identification.
This specification, which is not described in detail, partly belongs to common sense well known to those skilled in the art.
Claims (8)
1. a kind of quantum optimization method for aerospace optical remote sensing image, it is characterised in that include the following steps:
(1), satellite passes by and is imaged over the ground, using optical remote sensing imaging system, obtains the remote sensing image of observed object, goes forward side by side
Row normalized；
(2), normalized remote sensing image is transformed into vector subspace, decomposes on n quantum bit face, it is distant obtains optics
Feel quantum state vector of the image quantization information on each quantum bit face；
(3), optical remote sensing imaging system models are based on, using the method for norm optimization, by remote sensing image quantization information
Quantum state vector on each quantum bit face is filtered；
(4), the quantum state vector by filtered remote sensing image quantization information on each quantum bit face, is enhanced
Processing, obtains the quantum state vector on each quantum bit face of enhancingization；
(5), the quantum state vector reconstruction on each quantum bit face of enhancingization is converted into high-resolution remote sensing image.
2. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 1, it is characterised in that institute
Quantum state vector of the remote sensing image quantization information on each quantum bit face is stated to be expressed as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n]
In formula, pkThe corresponding quantization information of remote sensing image is represented in the probability amplitude in k-th of quantum bit face, | ψk(μ,ν)>
For the right arrow of the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face, < ψk(μ, ν) | be
The bra vector of the corresponding quantization information of remote sensing image quantum state vector in k-th of quantum bit face is | ψk(μ, ν) >
Conjugate transposition, (μ, ν) represent position coordinates of the quantum state vector on quantum bit face.
3. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 2, it is characterised in that institute
State the right arrow of the corresponding quantization information of image quantum state vector in k-th of quantum bit face | ψk(μ, ν) > expression formula are as follows:
In formula, | 0 > and | 1 > two ground state in image quantum bit are expressed as, f is the optical remote sensing figure after normalization
Picture, f (m, n) ∈ [0,1].
4. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 2, it is characterised in that when
In the case that image pixel value is according to exponential distribution probability distribution, the corresponding quantization information of described image is in k-th of quantum ratio
The right arrow of quantum state vector in special face | ψk(μ, ν) > expression formula are as follows:
In formula, θ and φ respectively indicate quantum bit and spatially correspond to vector and cartesian product coordinate system z-axis angle；Corresponding vector
The angle being projected between the cartesian product face coordinate system XOY and X-axis.
5. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 1, it is characterised in that institute
It states step (2) and uses " 2+p " norm optimization method, by quantum of the remote sensing image quantization information on each quantum bit face
State vector is filtered.
6. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 4, it is characterised in that institute
State " 2+p " norm optimization method are as follows: seek perfect optics remote sensing images I in the right arrow of k-th of quantum bit face quantum state vectorIt is allowed to meet following formula:
To by perfect optics remote sensing images I k-th of quantum bit face quantum state vector right arrowAs filter
Remote sensing image I after wave is calculated again later in the right arrow of k-th of quantum bit face quantum state vectorBe total to
Yoke transposition obtains filtered remote sensing image I in the bra vector of k-th of quantum bit face quantum state vector；
In formula,It is measured for the corresponding matrix H of optical remote sensing imaging system point spread function in k-th of quantum bit face
The right arrow of sub- state vector；
Quantum state of the normalized remote sensing image got for step (1) on k-th of quantum bit face
The right arrow of vector；
Indicate the right side of the quantum state vector on corresponding k-th of the quantum bit face optical remote sensing imaging system noise N
Arrow；
λkFor the regulation coefficient of each bit-plane, take between 0~1 here；2 norm minimums are sought in expression, | |
||pIndicate p norm, 0 < p < 1, ρkFor Dynamic gene, 0 < ρk< 1, DkFor gradient value, and formula is as follows:
In formula, | Fk(μ, ν) > for the pixel at remote sensing image (μ, ν) corresponding quantum bit on k-th of bit-plane
Value.
7. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 1, it is characterised in that institute
Stating step (4) is enhanced image using bilateral filtering method.
8. a kind of quantum optimization method for aerospace optical remote sensing image according to claim 1, it is characterised in that letter
Cease reconstructing method are as follows:
Wherein,It is the corresponding quantization information of enhanced remote sensing image in k-th of quantum bit face
The right arrow of quantum state vector,It is the corresponding quantization information of enhanced remote sensing image in k-th of quantum
The bra vector of quantum state vector in bit-plane isConjugate transposition；F'(m, n) be conversion after optical remote sensing figure
Picture.
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| CN112529812B (en) * | 2020-12-18 | 2022-12-02 | 西安微电子技术研究所 | Remote sensing image denoising method based on quantum Fourier transform |
| CN115761384A (en) * | 2023-01-09 | 2023-03-07 | 苏州浪潮智能科技有限公司 | Image classification method and device, electronic equipment and storage medium |
| CN116503620A (en) * | 2023-05-11 | 2023-07-28 | 中国科学院空天信息创新研究院 | High-resolution remote sensing image change detection method and device, electronic equipment and medium |
| CN116503620B (en) * | 2023-05-11 | 2023-12-08 | 中国科学院空天信息创新研究院 | High-resolution remote sensing image change detection method and device, electronic equipment and medium |
| CN117649613A (en) * | 2024-01-30 | 2024-03-05 | 之江实验室 | Optical remote sensing image optimization method and device, storage medium and electronic equipment |
| CN117649613B (en) * | 2024-01-30 | 2024-04-26 | 之江实验室 | Optical remote sensing image optimization method and device, storage medium and electronic equipment |
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