CN109753905B - Polarized SAR image target decomposition method based on expansion G4U - Google Patents

Abstract

The invention discloses a polarized SAR image target decomposition method based on expansion G4U, which comprises the following steps: based on a decision parameter related to the polarimetric SAR image target to be decomposed, a decomposition method which is best matched with the target is automatically selected between G4U and dual G4U according to the decision parameter, and the self-adaptive decomposition of the unknown target in the polarimetric SAR image is realized. The target decomposition method effectively combines G4U and dual G4U together through an adaptive selection strategy, realizes the maximization of complementary effects of the two and enables the identification and understanding of radar targets to be more accurate.

Description

Polarized SAR image target decomposition method based on expansion G4U

Technical Field

The invention relates to the field of polarized SAR image information processing, in particular to the field of polarized SAR target decomposition and model-based target decomposition, and specifically relates to a polarized SAR image target decomposition method based on expansion G4U.

Background

Model-based polarization decomposition is directed to polarizing coherence matrix [ T ] of unknown objects]And (4) expanding the standard scattering models to realize the identification and classification of the standard scattering models. Classical four-component model decomposition methods such as Y4R and S4R can only realize the pair coherence matrix [ T [ ]]For the explanation of seven degrees of freedom, two degrees of freedom remain unused, corresponding to T₁₃The real and imaginary parts of the components. To achieve this, Singh et al (G.Singh, Y.Yamaguchi, and S.E.park, "General four-component characterization power de-composition with free transformation of coherence matrix," IEEE Transactions on coherence and removal Sensing, vol.51, No.5, pp.3014-3022, May 2013) proposed in 2013 a G4U decomposition by introducing another unitary transformation that achieves the decomposition of T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.T.sub.₁₃Partial interpretation of the components, representing the latest level of the four component decomposition.

The core of the model decomposition is to solve a decomposition equilibrium equation set, and the conventional Y4R and S4R provide five equations for unknown parameters, but none of the equations involves a coherence matrix [ T]T of₁₃Component, therefore, pair T cannot be realized₁₃The effective use of (1). G4U forms one of five balance equations of Y4R and S4R by a mathematical unitary transform: f. of_Sβ+f_Dα+f_Vd＝T′₁₂Is divided into f_Sβ+f_Dα+f_Vd＝T′₁₂+T′₁₃And f_Sβ+f_Dα+f_Vd＝T′₁₂-T₁′₃Two equations, successfully sum T₁₃Component is taken to the right end of the equation, thereby bringing T to₁₃The fractions are used for the first time in a four-component decomposition. However, since the two equations are derived from bisection of the same equation, they are not completely independent of each other, so that the resulting balance equation set no longer has a unique solution. For this reason Singh et al only chose the equation f in G4U_Sβ+f_Dα+f_Vd＝T′₁₂+T′₁₃While abandoning the equation f_Sβ+f_Dα+f_Vd＝T′₁₂-T′₁₃. Our earlier studies showed that equation f_Sβ+f_Dα+f_Vd＝T′₁₂-T′₁₃And a reasonable solution can be provided, which and G4U just form a dual form, and dual G4U decomposition is developed on the basis of the reasonable solution, so that the decomposition defect of G4U is compensated, and a perfect complement to G4U is provided.

The complementary effect of G4U and dual G4U is reflected in that for some targets where G4U is not suitable, dual G4U is just better resolved; conversely, for some targets where dual G4U is not applicable, G4U may yield better decomposition. The problem is then how to know, without decomposing it, for an unknown target whether it applies to G4U or dual G4U, so that the complementary effects of G4U and dual G4U are exploited to the maximum.

Disclosure of Invention

The invention aims to effectively combine G4U and dual G4U together by an adaptive selection strategy to realize the maximum exertion of complementary effects of the two.

In order to achieve the above object, the present invention provides a polarized SAR image target decomposition method based on expansion G4U, the method including: based on a decision parameter related to the polarimetric SAR image target to be decomposed, a decomposition method which is best matched with the target is automatically selected between G4U and dual G4U according to the decision parameter, and the self-adaptive decomposition of the unknown target in the polarimetric SAR image is realized.

As an improvement of the above method, the method specifically comprises:

step 1) reading a coherent matrix [ T ] of a to-be-decomposed polarized SAR image, and executing de-orientation operation to obtain a de-oriented coherent matrix [ T' ];

step 2) removing orientation coherent matrix [ T 'based on the obtained step 1)']Calculating a decomposition parameter C, calculating a branch condition parameter BC based on C₁And BC₂；

Step 3) based on the parameters C, BC obtained in step 2)₁And BC₂Determining a decomposition parameter V, and further calculating a judgment parameter D based on V;

step 4) based on the decision parameter D obtained in step 3), if D is positive, G4U is executed to obtain surface scattering power P_STwo-sided scattered power P_DVolume scattering power P_VAnd helical scattered power P_C(ii) a Otherwise, executing dual G4U to obtain corresponding P_S、P_D、P_VAnd P_C。

As an improvement of the above method, in step 1), if the coherence matrix [ T ] of the polarized SAR image to be decomposed is

The desriented coherence matrix [ T' ] is:

wherein [ U ] is₃(θ)]Represent the SU (3) rotation matrix:

the orientation angle θ is estimated as follows:

as an improvement of the above method, in the step 2), the parameter C is calculated as follows:

C＝|Im{T′₂₃}|H(T′₃₃-|Im{T′₂₃}|)

where H (-) represents a unit step function:

wherein t is a variable;

based on parameter C, branch condition parameter BC₁And BC₂The calculation method of (2) is as follows:

as a modification of the above method, in the step 3), the method is based on C, BC₁And BC₂Calculating a decomposition parameter V:

the calculation method of the decision parameter D is as follows:

the invention has the advantages that:

1. the target decomposition method effectively combines G4U and dual G4U together through a self-adaptive selection strategy, and realizes the maximum exertion of complementary effects of the two;

2. in a two-side scattering dominant region, the expansion of G4U can obtain two-side scattering power larger than that of G4U and dual G4U; in the surface scattering dominant region, the surface scattering power is larger than that of G4U and dual G4U, the effect of 1+1>2 is realized, the decomposition of G4U and the decomposition of dual G4U are substantially improved, and the identification and understanding of radar targets are more accurate.

Drawings

FIG. 1 is a general flow chart of the polarized SAR image target decomposition method based on expansion G4U of the present invention;

FIG. 2 is a specific flowchart of the polarized SAR image target decomposition method based on expansion G4U according to the present invention;

FIG. 3 is a Pauli diagram of the coherence matrix [ T ] data of the polar SAR image to be decomposed employed in one embodiment of the present invention;

FIG. 4 shows the surface scattering power P obtained by decomposing the polarized SAR image by the method of the present invention in the embodiment of the present invention_SLogarithmic display (i.e. log)₁₀P_S)；

FIG. 5 shows the dihedral scattering power P obtained by decomposing the polarized SAR image by the method of the present invention in the embodiment of the present invention_DLogarithmic display (i.e. log)₁₀P_D)；

FIG. 6 shows the volume scattering power P obtained by decomposing the polarized SAR image by the method of the present invention in the embodiment of the present invention_VLogarithmic display (i.e. log)₁₀P_V)；

FIG. 7 shows the spiral scattering power P obtained by decomposing the polarized SAR image by the method of the present invention in the embodiment of the present invention_CLogarithmic display (i.e. log)₁₀P_C)；

FIG. 8 is a final result of the decomposition of the polarized SAR image by the method of the present invention in the embodiment of the present invention;

FIG. 9 is a diagram of the final selection of the G4U decomposition and the dual G4U decomposition in the method decomposition of the present invention on polarized SAR data in an embodiment of the present invention: white pixels represent the region for selecting G4U and black pixels represent the region for selecting dual G4U.

Detailed Description

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

Referring to fig. 1 and fig. 2, the method for decomposing the expansion G4U target of the polarized SAR image of the present invention includes the following steps:

step 1), reading in coherent matrix [ T ] data of a to-be-decomposed polarized SAR image, and executing orientation removing operation to obtain [ T' ];

step 2), obtaining a coherent matrix [ T 'based on the step 1)']Calculating a decomposition parameter C, calculating a branch condition parameter BC based on C₁And BC₂；

Step 3), based on the parameters C, BC obtained in step 2)₁And BC₂Determining a decomposition parameter V, and further calculating a judgment parameter D based on V;

step 4), based on the parameter D obtained in step 3), if D is positive, G4U is executed to obtain the surface scattering power P_STwo-sided scattered power P_DVolume scattering power P_VAnd helical scattered power P_C(ii) a Otherwise, executing dual G4U to obtain corresponding P_S、P_D、P_VAnd P_C。

The steps in the method of the present invention are further described below.

Reading in coherent matrix [ T ] data of a to-be-decomposed polarized SAR image in step 1), and performing de-orientation operation to obtain [ T' ]; in one embodiment, a Pauli diagram of read-in polarized SAR image coherence matrix [ T ] data to be decomposed is shown in FIG. 3, and the image size is 920 x 456, and the region of san Francisco USA is acquired by Canadian C-band Radarsat-2 radar 2008, 4/9. If the read-in target coherence matrix [ T ] is

The desriented target coherence matrix [ T' ] is calculated as follows:

wherein [ U ] is₃(θ)]Represent the SU (3) rotation matrix:

the orientation angle θ is estimated as follows:

based on the coherence matrix [ T' ] obtained in step 1), in step 2) we calculate the parameter C according to the following formula:

C＝|Im{T′₂₃}|H(T′₃₃-|Im{T′₂₃}|)

where H (-) represents a unit step function:

based on C, further calculating branch condition parameter BC₁And BC₂：

Based on the parameters C, BC obtained in step 2)₁And BC₂In step 3), first, a decomposition parameter V is calculated:

and further calculating a decision parameter D based on V:

d is a decision parameter related to the target itself, in step 4), the existing G4U or the dual G4U is selected adaptively according to the sign of the decision D to realize the decomposition of the target, and the surface scattering power P is calculated_STwo-sided scattered power P_DVolume scattering power P_VAnd helical scattered power P_CSo that the complementary effect of G4U and dual G4U is maximized. Specifically, if D is positive, G4U is executed to obtain P_S、P_D、P_VAnd P_C(ii) a Otherwise, executing dual G4U to obtain corresponding P_S、P_D、P_VAnd P_C。

FIGS. 4 to 7 show log-form surface scattering power log obtained by the method of the present invention on the polarized SAR data in the examples, respectively₁₀P_STwo-sided scattering power log₁₀P_DLog of bulk scattering power₁₀P_vAnd log of bulk scattering power₁₀P_C. Fig. 8 shows the final decomposition result obtained on the polarized SAR data in the embodiment of the method of the present invention.

Fig. 9 is a diagram showing the final selection of G4U decomposition and dual G4U decomposition in the extended G4U decomposition of the present invention on the polar SAR data in an embodiment: where white pixels represent the region where G4U was selected (i.e., parameter D >0), which covers 54.91% of the full map region; while the black pixels represent the region where the dual G4U was selected (i.e., parameter D ≦ 0), which covers the remaining 45.09% of the region, thus enabling adaptive decomposition of all potential target regions.

Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (1)

1. A polarized SAR image target decomposition method based on expansion G4U, the method comprising: based on a decision parameter related to the polarized SAR image target to be decomposed, automatically selecting a decomposition method which is best matched with the target between G4U and dual G4U according to the decision parameter, and realizing the self-adaptive decomposition of the unknown target in the polarized SAR image;

the method specifically comprises the following steps:

step 1) reading a coherent matrix [ T ] of a to-be-decomposed polarized SAR image, and executing de-orientation operation to obtain a de-oriented coherent matrix [ T' ];

step 2) removing orientation coherent matrix [ T 'based on the obtained step 1)']Calculating a decomposition parameter C, calculating a branch condition parameter BC based on C₁And BC₂；

Step 3) based on the parameters C, BC obtained in step 2)₁And BC₂Determining a decomposition parameter V, and further calculating a judgment parameter D based on V;

step 4) based on step 3) Obtaining a decision parameter D, if D is positive, executing G4U to obtain surface scattering power P_STwo-sided scattered power P_DVolume scattering power P_VAnd helical scattered power P_C(ii) a Otherwise, executing dual G4U to obtain corresponding P_S、P_D、P_VAnd P_C；

In step 1), if the coherent matrix [ T ] of the polarized SAR image to be decomposed is

The desriented coherence matrix [ T' ] is:

wherein [ U ] is₃(θ)]Represent the SU (3) rotation matrix:

the orientation angle θ is estimated as follows:

in the step 2), the calculation method of the parameter C is as follows:

C＝|Im{T′₂₃}|H(T′₃₃-|Im{T′₂₃}|)

where H (-) represents a unit step function:

wherein t is a variable;

based on parameter C, branch condition parameter BC₁And BC₂The calculation method of (2) is as follows:

in the step 3), based on C, BC₁And BC₂The calculated decomposition parameter V of (c):

the calculation method of the decision parameter D is as follows:

Images