CN110412573A - Polarimetric SAR image decomposition method and storage medium - Google Patents

Polarimetric SAR image decomposition method and storage medium Download PDF

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CN110412573A
CN110412573A CN201910728872.2A CN201910728872A CN110412573A CN 110412573 A CN110412573 A CN 110412573A CN 201910728872 A CN201910728872 A CN 201910728872A CN 110412573 A CN110412573 A CN 110412573A
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scattering
matrix
pixel
component
coherence matrix
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谭维贤
孙博绒
乞耀龙
黄平平
徐伟
高志奇
杨文�
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Inner Mongolia University of Technology
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Inner Mongolia University of Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/904—SAR modes
    • G01S13/9076—Polarimetric features in SAR
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9004—SAR image acquisition techniques
    • G01S13/9005—SAR image acquisition techniques with optical processing of the SAR signals

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  • General Physics & Mathematics (AREA)
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Abstract

The invention discloses a kind of polarimetric SAR image decomposition method and storage medium, which includes: the polarization coherence matrix T for obtaining full polarimetric SAR data；Judge the leading scattering mechanism in full polarimetric SAR data at each pixel, and the coherence matrix T at pixel is modified according to leading scattering mechanism, obtains revised coherence matrix T '；To revised four component goal decomposition of coherence matrix T ' carry out, the performance number of spiral volume scattering, volume scattering, surface scattering and even scattering is solved.The present invention carries out corresponding orientation angle compensation and phase angle rotation process according to the leading mechanism of pixel, considerably reduces the excessive estimation phenomenon of volume scattering, and solves the negative power phenomenon that surface scattering and even scattering generate；In addition, introducing adaptive volume scattering model adjustment, HH and VV component proportion consecutive variations can be made, make decomposition result closer to the scattering mechanism of practical ground object target.

Description

Polarimetric SAR image decomposition method and storage medium
Technical field
The present invention relates to microwave remote sensing technique field more particularly to a kind of polarimetric SAR image decomposition methods and storage medium.
Background technique
With the development of microwave remote sensing technique, polarimetric synthetic aperture radar (polarization SAR) has become microwave remote sensing field One important research direction gradually develops to multipolarization, multiband by single polarization, single band for the research of polarization SAR, in succession There is the full-polarization SARs system such as spaceborne, airborne.Polarization SAR has the electricity of horizontal polarization H or vertical polarization V by transmitting Magnetic wave is irradiated ground, and receives the scatter echo that the ground region has horizontal polarization H and vertical polarization V, to obtain Obtain the polarization scattering matrix of observation area.The details of observed object, including rough surface are contained in polarization scattering matrix The Electromagnetic Scattering Characteristics such as degree, orientation, symmetry, geometrical form.
Polarization target decomposition theory is proposed by Huynen earliest, is that a kind of pair of polarimetric SAR image data carries out target scattering The main method of feature extraction.Currently, polarimetric SAR image data decomposition method is mainly described the coherent target decomposition of pure target With the incoherent goal decomposition two major classes of description distributed object.Coherent target decomposition passes through the polarization scattering matrix to pure target It carries out addition or product is decomposed, extract a series of polarization characteristics that can preferably describe target, which mainly includes The methods of Pauli decomposition, Cameron decomposition, krogager decomposition.Incoherent goal decomposition is broadly divided into based on Mueller square Battle array incoherent goal decomposition, the incoherent goal decomposition of the characteristic value based on covariance matrix C or coherence matrix T and based on scattering The incoherent goal decomposition of model, the decomposition method specifically include that Cloude is decomposed, Freeman is decomposed, Yamaguchi is decomposed Deng.
Goal decomposition is a pith of polarization SAR, it is the antecedent basis of target classification, remote sensing application, can be with The physical mechanism of Scattering Targets is analyzed in help, is conducive to terrain classification, target identification of polarization SAR data etc..1998, Freeman and Durden first proposed ternary Polarization target decomposition method, is determined and is seen according to the polarization SAR data of acquisition Prevailing scattering mechanism in region is surveyed, original covariance matrix C or coherence matrix T are decomposed into three scattering ingredients The linear combination of (surface scattering, even scattering and volume scattering), this method assume that the rotation of dipole is uniform and reflection The establishment of symmetric condition.2005, Yamaguchi etc., the polarizing target point of four ingredients is proposed on Freeman decomposition base Solution method increases conveyor screw scattering ingredient.2009, Cloude proposed a kind of mixing Freeman/Eigenvalue decomposition Method, then decomposed thought be introduced into four component Models decompose in, incoherent goal decomposition obtained rapidly develop and extensively Using, but these methods are largely based on tri- ingredient breakdown of Cloude Eigenvalues Decomposition and Freeman, application has certain Limitation.
The existing maximum defect of scattering model decomposition method that is based on is exactly negative power problem.In radar system, give Transmitter and receiver, then the scattered power that receives directly proportional to radar cross section is unlikely to be negative forever, so Scattered power is impossible to be negative value under any circumstance.Negative scattered power Producing reason be due in decomposable process to it In a scattering component overestimate, since the sum of contribution of all scattering components is equal to the total work of coherence matrix received Rate, i.e. general power remain constant, if the power of a certain scattering component is overestimated at a certain pixel, in the pixel Locate remaining scattering component and is possible to the contribution for having negative.In addition, the presence of cross polarization power can reduce goal decomposition Accuracy, such as secondary area scattering couple the cross polarization power generated with volume scattering, and surface scattering couples generation with volume scattering Cross polarization power；In addition, traditional volume scattering model cannot carry out adaptive adjustment with the difference of polarization SAR data, It is not able to satisfy the consecutive variations demand of HH component and VV component proportion in forest land.
Summary of the invention
In view of the above-mentioned technical problems in the prior art, the technical problem to be solved is that offers for the embodiment of the present invention A kind of polarimetric SAR image decomposition method can reduce the excessively high estimation of volume scattering power, avoid even scattering and surface scattering Negative power is led to the problem of, to solve the problems, such as the existing negative power based in scattering model decomposition.
In order to solve the above-mentioned technical problem, the embodiment of the present invention adopts the technical scheme that
A kind of polarimetric SAR image decomposition method, includes the following steps:
S1: the polarization coherence matrix T of full polarimetric SAR data is obtained；
S2: judge the leading scattering mechanism in the full polarimetric SAR data at each pixel, and according to the master It leads scattering mechanism to be modified the coherence matrix T at the pixel, obtains revised coherence matrix T '；
S3: to the four component goal decomposition of coherence matrix T ' carry out after being corrected, spiral volume scattering is first solved respectively The performance number of component and volume scattering component, then, to decompositing the residual matrix after conveyor screw scattering component and volume scattering component TREigenvalues Decomposition is carried out, the performance number of surface scattering component and even scattering component is solved, completes four component goal decompositions.
Further, the coherence matrix T is 3 rank coherence matrix T3, each pixel includes 9 elements:
Wherein, t11, t12, t13, t21, t22, t23, t31, t32, t33Respectively indicate coherence matrix T3In 9 elements.
Further, the judgment method of the leading scattering mechanism at the pixel includes:
Enable Q=t11-t22, the Q value at pixel is calculated, is judged according to the size of Q value leading at each pixel Scattering mechanism,
Further, in step S2, being modified according to the leading scattering mechanism to the coherence matrix T includes: pair The coherence matrix T carries out orientation angle compensation and phase angle rotation.
Further, when surface scattering is dominated, the orientation angle compensation and phase angle rotation include:
Using formula (2) to the coherence matrix T3Orientation angle compensation is carried out, coherence matrix T is obtained3_1,
In formula, []HThe conjugate transposition of representing matrix,
Wherein, Re (t13) indicate to take real, tan-1Indicate arctan function；
Using formula (3) to through the compensated coherence matrix T in the azimuth3_1Phase angle rotation is carried out, phase is obtained Dry matrix T3_2,
In formula, []HThe conjugate transposition of representing matrix,
Wherein, Im (t13) indicate to take the imaginary part of plural number, tan-1Indicate arctan function, t11_1With t33_1It is T3_1In member Element；
When even scattering is leading, the orientation angle compensation and phase angle rotation include:
Using formula (4) to the coherence matrix T3Orientation angle compensation is carried out, coherence matrix T is obtained3_3,
In formula, []HThe conjugate transposition of representing matrix, R3It is as follows:
Wherein, Re (t23) indicate to take real part, tan-1Indicate arctan function；
Using formula (5) to through the compensated coherence matrix T in the azimuth3_3Phase angle rotation is carried out, phase is obtained Dry matrix T3_4,
In formula, []HThe conjugate transposition of representing matrix, R4It is as follows:
Wherein, Im (t23) indicate to take the imaginary part of plural number, tan-1Indicate arctan function；
The revised coherence matrix T ' is rotated through the orientation angle compensation and the phase angle3Final expression formula Are as follows:
Further, in step s3, according to formula (6) to the coherence matrix T '3Carry out four component goal decompositions:
In formula, TsRepresent surface scattering component, TdEven scattering component is represented,Represent volume scattering component, TcRepresent spiral shell Revolve volume scattering component, ms、md、mvAnd mcThe contribution margin of surface scattering, even scattering, volume scattering and spiral volume scattering is respectively indicated, Namely shared performance number.
Further, in step s3, according to the calculation formula (7) of conveyor screw scattering model, spiral volume scattering is calculated Performance number mc:
mc=2 | Im (t '23)| (7)
Wherein, t '23For T '3In element, the corresponding conveyor screw scattering model of conveyor screw scattering component are as follows:
Further, in step s3, volume scattering component is calculated according to the calculation formula (9) of volume scattering model
Wherein, γ=< | SHH|2>/<|SVV|2>, indicate the ratio between horizontal polarized components and perpendicular polarisation components；
Further, according to the rating formula (10) of volume scattering model, the performance number m of volume scattering component is calculatedv:
Wherein, < | SHV|2> for through the revised coherence matrix T ' of step S23Middle t '331/4 times of element.
Further, in step s3, to decompositing the residual matrix T after conveyor screw scattering component and volume scattering componentR Carry out Eigenvalues Decomposition:
And according to the judging result of the leading scattering mechanism at the pixel determined in the step S2, different masters are solved Lead the performance number m of the surface scattering component under scattering mechanismsWith the performance number m of even scattering componentd；
Wherein, include: according to the Eigenvalues Decomposition that the judging result of the leading scattering mechanism at the pixel carries out
Solution matrix TRCharacteristic value, acquire two eigenvalue λs1And λ2, enable λ1> λ2,
If judging Q > 0 at the pixel in step S2, i.e., when surface scattering is leading at the pixel, ms=λ1, md=λ2；
If judging Q≤0 at the pixel in step S2, i.e., when even scattering mechanism is leading at the pixel, ms=λ2, md =λ1。
The embodiments of the present invention also provide a kind of computer storage mediums, are stored thereon with computer executable instructions, When the computer executable instructions are executed by processor, above-mentioned polarimetric SAR image decomposition method is realized.
Compared with prior art, the beneficial effect of the embodiment of the present invention is: polarization SAR figure provided in an embodiment of the present invention As decomposition method, by judging the leading mechanism of pixel and carrying out corresponding orientation angle compensation and phase angle rotation process, greatly The amplitude reduction excessive estimation phenomenon of volume scattering；After decompositing conveyor screw scattering component and volume scattering component, using non-negative spy Value indicative method solves the power of surface scattering and even scattering, can be effectively solved the negative work that surface scattering and even scattering generate Rate phenomenon, and then obtain more accurate target scattering characteristics exploded view.In addition, when goal decomposition, the broad sense volume scattering of introducing Model no longer immobilizes, and can carry out adaptive adjustment with the difference of polarimetric SAR image data, meet in forest land The consecutive variations of HH component and VV component proportion can obtain class of more accurately classifying in the classification of different types of ground objects Not.
Detailed description of the invention
Fig. 1 is the flow chart of the polarimetric SAR image decomposition method of the embodiment of the present invention；
Fig. 2 is the flow chart of the polarimetric SAR image decomposition method of the embodiment of the present invention being modified to coherence matrix；
Fig. 3 is the flow chart of the four component power value of solution of the polarimetric SAR image decomposition method of the embodiment of the present invention.
Specific embodiment
Technical solution in order to enable those skilled in the art to better understand the present invention, with reference to the accompanying drawing and specific embodiment party Formula elaborates to the present invention.
It should be understood that various modifications can be made to disclosed embodiments.Therefore, description above should not regard To limit, and only as the example of embodiment.Those skilled in the art will expect in the scope and spirit of the present application Other modifications.
The attached drawing being included in the description and forms part of the description shows embodiments herein, and with it is upper What face provided is used to explain the application together to substantially description and the detailed description given below to embodiment of the application Principle.
By the description of the preferred form with reference to the accompanying drawings to the embodiment for being given as non-limiting example, the application's These and other characteristic will become apparent.
It is also understood that although the application is described referring to some specific examples, those skilled in the art Member realizes many other equivalents of the application in which can determine, they have feature as claimed in claim and therefore all In the protection scope defined by whereby.
When read in conjunction with the accompanying drawings, in view of following detailed description, above and other aspect, the feature and advantage of the application will become It is more readily apparent.
The specific embodiment of the application is described hereinafter with reference to attached drawing；It will be appreciated, however, that the disclosed embodiments are only Various ways implementation can be used in the example of the application.Known and/or duplicate function and structure and be not described in detail to avoid Unnecessary or extra details makes the application smudgy.Therefore, specific structural and functionality disclosed herein is thin Section is not intended to restrictions, but as just the basis of claim and representative basis be used to instructing those skilled in the art with Substantially any appropriate detailed construction diversely uses the application.
Fig. 1 is the flow chart of the polarimetric SAR image decomposition method of the embodiment of the present invention；As shown in Figure 1, this application provides A kind of polarimetric SAR image decomposition method, including step S1 to S3:
Step S1: the polarization coherence matrix T of full polarimetric SAR data is obtained；
In step sl, coherence matrix is obtained by carrying out data processing to the original full polarimetric SAR data of acquisition T.To obtain 3 rank coherence matrix T3For to polarization coherence matrix acquisition be illustrated, specific obtaining step includes:
Step S11: the polarization scattering matrix of original full polarimetric SAR data is obtained.
Full polarimetric SAR data can be indicated in the form of polarization scattering matrix, which is M*N rank, Wherein, M is number of data lines, and N is the columns of data；Pixel in full polarimetric SAR data at a certain position can be with i-th Row jth column position indicates, wherein (1, M) i ∈, i ∈ (1, N).
Specifically, full polarimetric SAR data are expressed as polarization back scattering matrix S,
Wherein, SHHAnd SVVContain the echo power in same polarization channel, SHVAnd SVHContain the echo in cross polarization channel Power, and meet reciprocal theorem SHV=SVH, the direction of propagation of H expression wave is horizontal (horizontal polarization), and V indicates the propagation side of wave Xiang Weiwei is vertical (vertical polarization).
Step S12: Scattering Targets vector is constructed from back scattering matrix SUnder multiple Pauli spin matrix set of bases Obtain corresponding " objective vector " are as follows:
WhereinRepresent the transposition of matrix；
Step S13: three rank coherence matrix T at each pixel are sought3, each pixel includes 9 elements, expression Formula are as follows:
In formula, t11, t12, t13, t21, t22, t23, t31, t32, t33Indicate 9 elements in coherence matrix, []*Representing matrix Conjugation, []HThe conjugate transposition of representing matrix,<>indicate that view number is average,Indicate target vector itself conjugate transposition The apposition of vector.
It preferably, before step S12, i.e., further include to polarization before carrying out data processing to polarization scattering matrix S Collision matrix S carries out Lee filtering, to remove the influence of noise.In addition, since the filtering can preferably keep local edge, because This it can also reduce due to negative power problem caused by filtering.
Step S2: judge the leading scattering mechanism in full polarimetric SAR data at each pixel, and according to the pixel Leading scattering mechanism at point is modified the coherence matrix T at the pixel；
Fig. 2 is the flow chart of the polarimetric SAR image decomposition method of the embodiment of the present invention being modified to coherence matrix, such as Shown in Fig. 2, in step s 2, the method judged the leading scattering mechanism of pixel at the i-th row jth column position includes:
Enable Q=t11-t22, the Q value at the pixel is calculated, the leading of each pixel position is judged according to the size of Q value Scattering mechanism, specific judgment method are shown below:
Further, according to the leading scattering mechanism at pixel coherence matrix is modified including orientation angle compensation and Phase angle rotation.According to the difference of the leading scattering mechanism at pixel, using different formula to being concerned at the phase vegetarian refreshments Matrix successively carries out orientation angle compensation and phase angle rotation, to coherence matrix T3It is modified.
Specifically, if judging the Q > 0 of pixel at the i-th row jth column position, wherein (1, M) i ∈, i ∈ (1, N) then should Surface scattering accounts for leading at pixel, to the coherence matrix T at the pixel3Orientation angle compensation and the specific packet of phase angle rotation It includes:
(1) orientation angle compensation
Specifically, to coherence matrix T3It proceeds as follows, obtains the compensated coherence matrix T in azimuth3_1, specific to grasp Make as shown in formula (2):
Wherein, []HThe conjugate transposition of representing matrix, R1It is as follows:
Wherein, Re (t13) indicate to take real, tan-1Indicate arctan function；
(2) phase angle rotates
Specifically, to through the compensated coherence matrix T in above-mentioned azimuth3_1It proceeds as follows, after obtaining phase angle rotation Coherence matrix T3_2, shown in concrete operations such as formula (3):
Wherein, []HThe conjugate transposition of representing matrix, R2It is as follows:
Wherein, Im (t13) indicate to take the imaginary part of plural number, tan-1Indicate arctan function, t11_1With t33_1It is T3_1In member Element.
If judging Q≤0 of pixel at the i-th row jth column position, wherein (1, M) i ∈, i ∈ (1, N), then at the pixel Even scattering account for it is leading, to the coherence matrix T at the pixel3Orientation angle compensation and phase angle rotation specifically include:
(1) orientation angle compensation
Specifically, to coherence matrix T3It proceeds as follows, obtains the compensated coherence matrix T in azimuth3_3, specific to grasp Make as shown in formula (4):
Wherein, []HThe conjugate transposition of representing matrix, R3It is as follows:
Wherein, Re (t23) indicate to take real part, tan-1Indicate arctan function；
(2) phase angle rotates
To through the compensated coherence matrix T in above-mentioned azimuth3_3It proceeds as follows, it is postrotational relevant to obtain phase angle Matrix T3_4, shown in concrete operations such as formula (5):
Wherein, []HThe conjugate transposition of representing matrix, R4It is as follows:
Wherein, Im (t23) indicate to take the imaginary part of plural number, tan-1Indicate arctan function.
By the coherence matrix T ' after step S2 correcting process3It may finally indicate are as follows:
Wherein,
Specifically, coherence matrix T3_2With coherence matrix T3_4Expression formula be respectively as follows:
The leading scattering mechanism at different pixels point is judged using determining method, and passes through phase angle rotation and orientation Coherence matrix is modified to compensation, can more targetedly eliminate cross polar component HV, reduce surface scattering and The negative power problem of even scattering.
Fig. 3 shows the solution of four component powers in the step S3 of the polarimetric SAR image decomposition method of the embodiment of the present invention Flow chart.As shown in figure 3, step S3 includes: first to divide the four component goal decomposition of polarization coherence matrix T ' carry out after being corrected Not Qiu Xie conveyor screw scattering component and volume scattering component performance number, then, to decompositing conveyor screw scattering component and volume scattering Residual matrix T after componentREigenvalues Decomposition is carried out, the performance number of surface scattering component and even scattering component is solved, is completed Four component goal decompositions.
Coherence matrix T '3Divide solution's expression as follows:
Wherein, TsRepresent surface scattering component, TdEven scattering component is represented,Represent volume scattering component, TcRepresent spiral shell Revolve volume scattering component, ms、md、mvAnd mcThe contribution margin of surface scattering, even scattering, volume scattering and spiral volume scattering is respectively indicated, Namely shared performance number.
In step s3, to the polarization coherence matrix T ' after being corrected3The method for carrying out four component goal decompositions is specifically wrapped Include following steps:
Step S31: the performance number m of conveyor screw scattering component is solved respectivelycWith the performance number m of volume scattering componentv。
Specifically, according to the calculation formula (7) of conveyor screw scattering model, the performance number m of spiral volume scattering is calculatedc:
mc=2 | Im (t '23)| (7)
Wherein, t '23For T '3In element, the corresponding conveyor screw scattering model of conveyor screw scattering component are as follows:
The coherence matrix T ' after processing is corrected according to step S23, utilize the calculation formula (9) of volume scattering model, meter Calculate the generalized body scattering model component of pixel
Wherein, γ=< | SHH|2>/<|SVV|2>, indicate the ratio between horizontal polarized components and perpendicular polarisation components；
Further, according to the rating formula (10) of volume scattering model, the performance number m of volume scattering component is calculatedv:
Wherein, < | SHV|2> for through the revised coherence matrix T ' of step S23Middle t '331/4 times of element.
In step S31, the performance number m of conveyor screw scattering component is solvedcWith the performance number m of volume scattering componentvSequence not It is specific to limit.Goal decomposition is carried out to the volume scattering in polarization decomposing using the volume scattering model of above-mentioned formula (9), in certain journey Surface scattering and dihedral angle scattering caused by being overestimated due to volume scattering power are alleviated on degree negative power problem occurs；Separately Outside, the gamma parameter γ in above-mentioned volume scattering model can be with modified coherence matrix T3' variation and change, can As the difference of polarimetric SAR image data carries out adaptive adjustment, the company of HH component and VV component proportion in forest land is met Continuous variation, can obtain more accurate class categories in the classification of different types of ground objects, nicety of grading be improved, so that target Scattering mechanism of the decomposition result closer to practical ground object target.
Step S32: to decompositing the residual matrix T after conveyor screw scattering component and volume scattering componentRCarry out characteristic value point Solution solves the performance number m of surface scattering componentsWith the performance number m of even scattering componentd, complete four component goal decompositions.
Through the revised coherence matrix T ' of step S23Subtract the volume scattering component that step S31 is decompositedAnd spiral Volume scattering component mcTcAs residual matrix TR, residual matrix TRFor the sum of surface scattering and even scattering component:
After the contribution for determining conveyor screw scattering component and volume scattering component, residual matrix T is solvedRCharacteristic value, and According to the judging result of the leading scattering mechanism at the pixel determined in step S2, solve under different leading scattering mechanisms The performance number m of surface scattering componentsWith the performance number m of even scattering componentd。
Specifically, solution matrix TRCharacteristic value, acquire λ1And λ2Two characteristic values, enable λ1> λ2,
If judging Q > 0 at the pixel in step S2, i.e., when surface scattering is leading, ms=λ1, md=λ2；
If judging Q≤0 at the pixel in step S2, i.e., when even scattering mechanism is leading, ms=λ2, md=λ1。
Above-mentioned matrix TRSolution procedure in, surface scattering model TsWith even scattering model TdIt is hybrid freeman Known model in decomposition, details are not described herein.
The performance number m of volume scattering model formation (9) and solution volume scattering component in step S31vCalculation formula (10), it is ensured that residual matrix TRBe an order it is 2, and keeps the matrix of positive semidefinite, it can guarantees that the surface solved dissipates Penetrating with even scattering is nonnegative number.
After the performance numbers that step S3 calculates in polarimetric SAR image four kinds of scatterings, according to entire polarization SAR is calculated The power m of surface scattering, even scattering, volume scattering and spiral volume scattering in images、md、mvWith mc value, it is pseudo- color that RGB can be generated Color composite diagram.
Specifically, the power m of secondary secondary scattering component is indicated with red Rd, the power m of green G expression volume scattering componentvWith The power m of conveyor screw scattering componentc, the power m of blue B expression surface scattering components, a width is obtained using RGB synthetic method Pseudocolour picture after polarimetric SAR image decomposition.
Since spiral volume scattering belongs to special volume scattering, and its performance number is smaller, therefore, can will when composograph The power m of conveyor screw scattering componentcIt is incorporated to the power m of volume scattering componentvIn.
Below with the German area Oberpfaffenhofen L-band ESAR on-board data as test data, and use Matlab software verifies four component decomposition method of polarization of the invention.In verification test, Freeman decomposition is respectively adopted Method and mixing Freeman/Eigenvalue decomposition method compare test, and calculate the pixel quantity of negative power, verify The results are shown in Table 1.
The negative power pixel ratio of 1 three kinds of decomposition methods of table
By above-mentioned verification test result it is found that using polarimetric SAR image decomposition method provided by the invention, can effectively solve The certainly negative power problem during goal decomposition.
Polarimetric SAR image decomposition method provided in an embodiment of the present invention, by the leading mechanism and the progress that judge pixel Corresponding orientation angle compensation and phase angle rotation process, considerably reduce the excessive estimation phenomenon of volume scattering；Decomposite spiral After volume scattering component and volume scattering component, the power of surface scattering and even scattering, Neng Gouyou are solved using non-negative method of characteristic The negative power phenomenon for solving surface scattering and even scattering and generating of effect, and then obtain more accurate target scattering characteristics and decompose Figure.In addition, the generalized body scattering model of introducing no longer immobilizes when goal decomposition, it can be with polarimetric SAR image number According to difference carry out adaptive adjustment, meet the consecutive variations of HH component and VV component proportion in forest land, can be differently More accurate class categories are obtained in the classification of species type.
The embodiments of the present invention also provide a kind of computer storage mediums, are stored thereon with computer executable instructions, When the computer executable instructions are executed by processor, the polarimetric SAR image in above-mentioned embodiment according to the present invention is realized Decomposition method.
In some embodiments, executing calculation machine executable instruction processor can be including more than one general purpose processing device Processing equipment, microprocessor, central processing unit (CPU), graphics processing unit (GPU) etc..More specifically, the processing Device can be complex instruction set calculation (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) the combined processor of microprocessor, the processor or operating instruction collection that run other instruction set.The processor may be used also To be more than one dedicated treatment facility, such as specific integrated circuit (ASIC), field programmable gate array (FPGA), number letter Number processor (DSP), system on chip (SoC) etc..
In some embodiments, computer readable storage medium can be memory, such as read-only memory (ROM), with Machine accesses memory (RAM), phase change random access memory devices (PRAM), static random access memory (SRAM), dynamic random Access memory (DRAM), electrically erasable programmable read-only memory (EEPROM), other kinds of random access memory (RAM), flash disk or the flash memory of other forms, caching, register, static memory, compact disc read-only memory (CD-ROM), number Word general optic disc (DVD) or other optical memory, cassette tape or other magnetic storage apparatus, or be used to store and can be counted Calculate the medium etc. of the information of machine equipment access or any other possible non-transitory of instruction.
In some embodiments, computer executable instructions can be implemented as multiple program modules, and multiple program modules are total With the polarimetric SAR image decomposition method realized in above-mentioned embodiment according to the present invention.
Above embodiments are only exemplary embodiment of the present invention, are not used in the limitation present invention, protection scope of the present invention It is defined by the claims.Those skilled in the art can within the spirit and scope of the present invention make respectively the present invention Kind modification or equivalent replacement, this modification or equivalent replacement also should be regarded as being within the scope of the present invention.

Claims (10)

1. a kind of polarimetric SAR image decomposition method, which comprises the steps of:
S1: the polarization coherence matrix T of full polarimetric SAR data is obtained；
S2: judge the leading scattering mechanism in the full polarimetric SAR data at each pixel, and according to described leading scattered It penetrates mechanism to be modified the coherence matrix T at the pixel, obtains revised coherence matrix T '；
S3: to the four component goal decomposition of coherence matrix T ' carry out after being corrected, conveyor screw scattering component is first solved respectively With the performance number of volume scattering component, then, to decompositing the residual matrix T after conveyor screw scattering component and volume scattering componentRInto Row Eigenvalues Decomposition solves the performance number of surface scattering component and even scattering component, completes four component goal decompositions.
2. polarimetric SAR image decomposition method according to claim 1, which is characterized in that the coherence matrix T is 3 rank phases Dry matrix T3, each pixel includes 9 elements:
Wherein, t11, t12, t13, t21, t22, t23, t31, t32, t33Respectively indicate coherence matrix T3In 9 elements.
3. polarimetric SAR image decomposition method according to claim 2, which is characterized in that leading scattered at the pixel The judgment method for penetrating mechanism includes:
Enable Q=t11-t22, the Q value at pixel is calculated, the leading scattering at each pixel is judged according to the size of Q value Mechanism,
4. polarimetric SAR image decomposition method according to claim 3, which is characterized in that in step S2, according to described leading It includes: to carry out orientation angle compensation and phase angle rotation to the coherence matrix T that scattering mechanism, which is modified the coherence matrix T, Turn.
5. polarimetric SAR image decomposition method according to claim 4, which is characterized in that
When surface scattering is dominated, the orientation angle compensation and phase angle rotation include:
Using formula (2) to the coherence matrix T3Orientation angle compensation is carried out, coherence matrix T is obtained3_1,
In formula, []HThe conjugate transposition of representing matrix,
Wherein, Re (t13) indicate to take real, tan-1Indicate arctan function；
Using formula (3) to through the compensated coherence matrix T in the azimuth3_1Phase angle rotation is carried out, relevant square is obtained Battle array T3_2,
In formula, []HThe conjugate transposition of representing matrix,
Wherein, Im (t13) indicate to take the imaginary part of plural number, tan-1Indicate arctan function, t11_1With t33_1It is T3_1In element；
When even scattering is leading, the orientation angle compensation and phase angle rotation include:
Using formula (4) to the coherence matrix T3Orientation angle compensation is carried out, coherence matrix T is obtained3_3,
In formula, []HThe conjugate transposition of representing matrix, R3It is as follows:
Wherein, Re (t23) indicate to take real part, tan-1Indicate arctan function；
Using formula (5) to through the compensated coherence matrix T in the azimuth3_3Phase angle rotation is carried out, relevant square is obtained Battle array T3_4,
In formula, []HThe conjugate transposition of representing matrix, R4It is as follows:
Wherein, Im (t23) indicate to take the imaginary part of plural number, tan-1Indicate arctan function；
The revised coherence matrix T ' is rotated through the orientation angle compensation and the phase angle3Final expression formula are as follows:
6. polarimetric SAR image decomposition method according to claim 5, which is characterized in that in step s3, according to formula (6) to the coherence matrix T '3Carry out four component goal decompositions:
In formula, TsRepresent surface scattering component, TdEven scattering component is represented,Represent volume scattering component, TcRepresent conveyor screw Scattering component, ms、md、mvAnd mcThe contribution margin of surface scattering, even scattering, volume scattering and spiral volume scattering is respectively indicated, namely Shared performance number.
7. polarimetric SAR image decomposition method according to claim 6, which is characterized in that in step s3, according to conveyor screw The calculation formula (7) of scattering model calculates the performance number m of spiral volume scatteringc:
mc=2 | Im (t '23)| (7)
Wherein, t '23For T '3In element, the corresponding conveyor screw scattering model of conveyor screw scattering component are as follows:
8. polarimetric SAR image decomposition method according to claim 7, which is characterized in that in step s3, according to volume scattering The calculation formula (9) of model calculates volume scattering component
Wherein, γ=< | SHH|2>/<|SVV|2>, indicate the ratio between horizontal polarized components and perpendicular polarisation components；
Further, according to the rating formula (10) of volume scattering model, the performance number m of volume scattering component is calculatedv:
Wherein, < | SHV|2> for through the revised coherence matrix T ' of step S23Middle t '331/4 times of element.
9. polarimetric SAR image decomposition method according to claim 8, which is characterized in that in step s3, to decompositing spiral shell Residual matrix T after revolving volume scattering component and volume scattering componentRCarry out Eigenvalues Decomposition:
And according to the judging result of the leading scattering mechanism at the pixel determined in the step S2, solve different leading scattered Penetrate the performance number m of the surface scattering component under mechanismsWith the performance number m of even scattering componentd；
Wherein, include: according to the Eigenvalues Decomposition that the judging result of the leading scattering mechanism at the pixel carries out
Solution matrix TRCharacteristic value, acquire two eigenvalue λs1And λ2, enable λ1> λ2,
If judging Q > 0 at the pixel in step S2, i.e., when surface scattering is leading at the pixel, ms=λ1, md=λ2；
If judging Q≤0 at the pixel in step S2, i.e., when even scattering mechanism is leading at the pixel, ms=λ2, md=λ1。
10. a kind of storage medium, which is characterized in that be stored thereon with computer executable instructions, the computer is executable to be referred to When order is executed by processor, polarimetric SAR image decomposition method according to claim 1 to 9 is realized.
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