CN104569945A - Self-adaptive filtering method used for SAR (synthetic aperture radar) image - Google Patents

Self-adaptive filtering method used for SAR (synthetic aperture radar) image Download PDF

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CN104569945A
CN104569945A CN201410830069.7A CN201410830069A CN104569945A CN 104569945 A CN104569945 A CN 104569945A CN 201410830069 A CN201410830069 A CN 201410830069A CN 104569945 A CN104569945 A CN 104569945A
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sar image
image data
speckle noise
dimentional
homomorphism
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刘李娟
李秀华
李宏宇
高希权
李闯
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Beijing Institute of Radio Metrology and Measurement
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Beijing Institute of Radio Metrology and Measurement
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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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • 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
    • G01S13/9021—SAR image post-processing techniques
    • G01S13/9027—Pattern recognition for feature extraction
    • 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

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention discloses a self-adaptive filtering method used for an SAR (synthetic aperture radar) image. The method comprises steps as follows: SAR image data containing speckle noise are sequentially subjected to logarithm transformation and azimuth and range two-dimension Fourier transformation to obtain SAR image data containing speckle noise in a two-dimensional cepstrum domain; the image data in the two-dimensional cepstrum domain are subjected to filtering with a two-dimensional rectangular window function; the filtered image data in the two-dimensional cepstrum domain are sequentially subjected to azimuth and range two-dimensional Fourier inversion transformation and exponential transformation to obtain the SAR image data with inhibited speckle noise. The self-adaptive filtering method inhibits the speckle noise of the SAR image more effectively, and the quality of a radar image is improved.

Description

A kind of adaptive filter method for the synthesis of aperture radar image
Technical field
The present invention relates to a kind of filtering method.More specifically, a kind of adaptive filter method for the synthesis of aperture radar (SAR, Synthetic Aperture Radar) image is related to.
Background technology
The existence of speckle noise makes the remote sensing images of synthetic-aperture radar correctly can not reflect the scattering properties of ground object target, not only increases the complicacy of user's interpretation, and easily causes erroneous judgement, reduce SAR to target detection, analysis and interpretability; Have also increased dramatically the difficulty of SAR image quantification application.On the other hand, along with the continuous expansion of SAR image application, require to improve constantly to its space, radiometric resolution, also more and more higher to the suppression level requirement of speckle noise.Effectively suppressing or eliminating SAR image speckle noise is improve radar image quality, SAR image data are succeeded the basis of application.
The model that traditional most filtering algorithm is set up is all Additive noise model, as Wiener filtering, medium filtering, mean filter scheduling algorithm, and the intrinsic speckle noise of synthetic-aperture radar belongs to multiplicative noise, utilizes traditional filtering algorithm often can not effectively suppress SAR speckle noise.
Therefore, need to provide a kind of adaptive filter method for the synthesis of aperture radar image.
Summary of the invention
The object of the present invention is to provide a kind of adaptive filter method for the synthesis of aperture radar image.
For achieving the above object, the present invention adopts following technical proposals:
For the synthesis of an adaptive filter method for aperture radar SAR image, the method comprises the steps:
S1, carry out log-transformation to containing the SAR image data of speckle noise, obtain the SAR image data of homomorphism territory containing speckle noise;
S2, to homomorphism territory containing the SAR image data of speckle noise carry out orientation to distance to two-dimensional Fourier transform, obtain the SAR image data of two-dimentional cepstrum domain containing speckle noise;
S3, utilizing two-dimensional rectangle window function to carry out filtering to two-dimentional cepstrum domain containing the SAR image data of speckle noise, obtaining the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing;
S4, to two-dimentional cepstrum domain speckle noise through suppress SAR image data carry out orientation to distance to two-dimentional inverse Fourier transform, obtain homomorphism territory speckle noise through suppress SAR image data;
S5, to homomorphism territory speckle noise through suppress SAR image data carry out exponential transform, obtain speckle noise through suppress SAR image data.
Preferably, step S3 comprises following sub-step further:
S3.1, set the length of rectangular window and the initial value of width in two-dimensional rectangle window function respectively at two-dimentional cepstrum domain, and set the length of rectangular window and the convergence step-length of width in two-dimensional rectangle window function respectively;
S3.2, rectangular window function is utilized to carry out filtering to two-dimentional cepstrum domain containing the SAR image data of speckle noise and the entropy of view data after calculation of filtered;
S3.3, reduce length and the width of rectangular window in two-dimensional rectangle window function respectively according to the convergence step-length of the length of rectangular window in two-dimensional rectangle window function and width;
S3.4, iterative step S3.2 and step S3.3, until the entropy of filtered image data no longer reduces, obtain the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing.
Preferably, in step S3.1 in two-dimensional rectangle window function the length of rectangular window and the initial value of width be set as respectively orientation in step S2 to the dimension of Fourier transform 1/2nd and dimension from distance to Fourier transform 1/2nd.
Preferably, in step S3.1 in two-dimensional rectangle window function the length of rectangular window and the convergence step-length of width be set as respectively orientation in step S2 to the dimension of Fourier transform 1/10th and dimension from distance to Fourier transform 1/10th.
Preferably, in step S2 to homomorphism territory containing the SAR image data of speckle noise carry out orientation to distance to the formula of two-dimensional Fourier transform be:
G ( k 1 , k 2 ) = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ I ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ S ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } + Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ w ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) }
In formula, x represent orientation to, y represent distance to, I (x, y) is the SAR image data containing speckle noise, log 10(I (x, y)), for homomorphism territory is containing the SAR image data of speckle noise, S (x, y) is not containing the SAR image data of speckle noise, log 10(S (x, y)), for homomorphism territory is not containing the SAR image data of speckle noise, w (x, y) is speckle noise data, log 10(w (x, y)) is homomorphism territory speckle noise data, and j represents imaginary number, k 1for with orientation to orientation corresponding to x to cepstrum variable, k 2for with distance to distance corresponding to y to cepstrum variable, N 1for orientation is to dimension, the N of Fourier transform 2for distance is to the dimension of Fourier transform, G (k 1, k 2) for two-dimentional cepstrum domain is containing the SAR image data of speckle noise.
Preferably, the formula utilizing two-dimensional rectangle window function to carry out filtering to two-dimentional cepstrum domain containing the SAR image data of speckle noise in step S3 is as follows:
G`(k 1,k 2)＝H(k 1,k 2)G(k 1,k 2)
In formula, G` (k 1, k 2) be the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing, H (k 1, k 2) be two-dimensional rectangle window function.
Preferably, two-dimensional rectangle window function H (k 1, k 2) function formula as follows:
H ( k 1 , k 2 ) = rect ( k 1 l 1 ) rect ( k 2 l 2 )
In formula, l 1for the length of rectangular window in two-dimensional rectangle window function, l 2for the width of rectangular window in two-dimensional rectangle window function, rect represents rectangular function.
Preferably, in step S4 to the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing carry out orientation to distance to the formula of two-dimentional inverse Fourier transform be:
g ` ( x , y ) = 1 N 1 N 2 Σ k 1 = 0 N 1 - 1 Σ k 2 = 0 N 2 - 1 G ` ( k 1 , k 2 ) exp { + j 2 π ( k 1 x N 1 + k 2 y N 2 ) }
In formula, g` (x, y) is the SAR image data of homomorphism territory speckle noise through suppressing.
Preferably, in step S5 to the formula that the SAR image data of homomorphism territory speckle noise through suppressing carry out exponential transform be:
I`(x,y)＝exp(g`(x,y))
In formula, I` (x, y) is the SAR image data of speckle noise through suppressing.
Beneficial effect of the present invention is as follows:
Technical scheme of the present invention solves in SAR image the problem suppressing speckle noise, compared with traditional filtering method, have following two key features: one be by the SAR image data transformation of Noise to two-dimentional cepstrum domain, effectively radar image and speckle noise are made a distinction at two-dimentional cepstrum domain.Be by first SAR image data separate log-transformation being transformed to homomorphism territory by SAR image data transformation to two-dimentional cepstrum domain, then carry out two-dimensional Fourier transform in homomorphism territory SAR image is transformed to two-dimentional cepstrum domain.Speckle noise through isomorphic transformation multiplicative is transformed into additive noise, and SAR image at two-dimentional cepstrum domain mainly at low frequency speckle noise then at high frequency, effectively speckle noise can be separated by rectangular window function during filtering at two-dimentional cepstrum domain like this; Two is utilize entropy to judge filter effect when filtering, reaches optimum filtering effect by calculating whether minimum the judging whether of entropy.By comparing with the filter effect of traditional filtering algorithm based on frequency domain, technical scheme of the present invention more effectively suppresses the speckle noise of SAR image data, improves the quality of radar image.
Accompanying drawing explanation
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
Fig. 1 illustrates the process flow diagram of the adaptive filter method for the synthesis of aperture radar image.
Fig. 2-a to 2-f illustrates the design sketch of the adaptive filter method for the synthesis of aperture radar image.
Embodiment
In order to be illustrated more clearly in the present invention, below in conjunction with preferred embodiments and drawings, the present invention is described further.Parts similar in accompanying drawing represent with identical Reference numeral.It will be appreciated by those skilled in the art that specifically described content is illustrative and nonrestrictive, should not limit the scope of the invention with this below.
The adaptive filter algorithm for the synthesis of aperture radar image that the present embodiment provides utilizes MATLAB to realize.The SAR image adopted is from the RADARSAT-1 raw data of Vancouver scene.This data acquisition was on June 16th, 2002, and data parameters is in table 1.
The RADARSAT-1 parameter of table 1 Vancouver scene is summed up
Parameter Symbol Value Unit
Sampling rate F r 32.317 MHz
Bandwidth B r 30.111 MHz
Pulse center frequencies 0 MHz
Distance frequency modulation rate K r 0.72135 MHz/μs
Pulsewidth T r 41.74 μs
Radar frequency f 0 5.300 GHz
Radar wavelength λ 0.05657 m
Pulse repetition rate F a 1256.98 Hz
Effective radar speed V r 7062 m/s
Orientation frequency modulation rate K a 1733 Hz/s
Doppler centroid f nc -6900 Hz
Imaging is carried out to these data.SAR image after imaging is as the input utilized based on two-dimentional cepstrum domain adaptive filter method, and method is as follows:
The adaptive filter algorithm for the synthesis of aperture radar image that the present embodiment provides, concrete steps are:
The model formation of step 1, the SAR raw image data of foundation containing speckle noise.If the original SAR image data containing speckle noise are I (x, y), SAR image data not containing speckle noise are S (x, y), speckle noise data are w (x, y), the speckle noise due to SAR image is that multiplicative is independent identically distributed, therefore the original SAR image model formation containing speckle noise is:
I (x, y)=S (x, y) w (x, y) formula (1)
In formula, x represent orientation to, y represent distance to.
SAR image data are plural number, and by carrying out log-transformation to view data, image data transformation is become the view data in homomorphism territory, be converted to the multiplication relationship of speckle noise the relation of addition by SAR image, formula is as follows:
Log 10[I (x, y)]=log 10[S (x, y)]+log 10[w (x, y)] formula (2)
In formula, log 10[I (x, y)] for homomorphism territory is containing the SAR image data of speckle noise, log 10[S (x, y)], for homomorphism territory is not containing the SAR image data of speckle noise, w (x, y) is speckle noise data, log 10[w (x, y)] is homomorphism territory speckle noise data.
Step 2, the view data in homomorphism territory carried out orientation to distance to two-dimensional Fourier transform, the image data transformation in homomorphism territory is become the view data of two-dimentional cepstrum domain.Explanation for cepstrum domain is: the view data in homomorphism territory transforms to a new territory after Fourier transform, is called cepstrum domain.The formula view data in homomorphism territory being carried out to two-dimensional Fourier transform is as follows:
G ( k 1 , k 2 ) = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ I ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ S ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } + Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ w ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } Formula (3)
In formula, j represents imaginary number, k 1for with orientation to orientation corresponding to x to cepstrum variable, k 1for with distance to distance corresponding to y to cepstrum variable, N 1for orientation is to the dimension of Fourier transform, N 2for distance is to the dimension of Fourier transform, G (k 1, k 2) be the SAR image data of two-dimentional cepstrum domain, can see from formula and have passed log-transformation and two-dimensional Fourier transform, the two-dimentional cepstrum of the SAR image of Noise is divided into effectively the cepstrum of original SAR image cepstrum and noise, due to the cepstrum of SAR image, mainly at low frequency, the cepstrum of noise, mainly at high frequency, therefore can be filtered by the cepstrum of filtering by noise at cepstrum domain effectively.
Step 3, at two-dimentional cepstrum domain setting two-dimensional rectangle window length and width n 1, n 2initial value, and the convergence step-length setting rectangular window length and width is respectively Δ n 1with Δ n 2, utilize rectangular window to carry out filtering to two-dimentional cepstrum domain data, then the entropy of image after calculation of filtered, to restrain step delta n 1, Δ n 2reduce length and the width of rectangular window respectively, the entropy of computed image after filtering, catch up with the entropy once calculated and compare entropy and whether reduce, if reduce, then to restrain step delta n 1, Δ n 2continue the length and the width that reduce window respectively, until entropy no longer reduces, think that spectral window is optimum window.If two-dimensional rectangle window function is H (k 1, k 2), then the view data G` (k of two-dimentional cepstrum domain after filtering 1, k 2) can be expressed as:
G` (k 1, k 2)=H (k 1, k 2) G (k 1, k 2) formula (4)
H (k in formula 1, k 2) be rectangular window function, can be expressed as
H ( k 1 , k 2 ) = rect ( k 1 n 1 - m * Δ n 1 ) rect ( k 2 n 2 - m * Δ n 2 ) Formula (5)
In formula, m is the number of times of iteration, with for rectangular function, be defined as:
In formula, n 1, n 2the initial length of two-dimensional rectangle window when being respectively filtering and width.Two-dimensional rectangle window length and width n are being set 1, n 2initial value and convergence step delta n 1, Δ n 2in time, should be noted: if initial value is established larger, and convergence step-length is established less, then need more number of times could obtain optimum window, comparatively time-consuming, and if initial value is established less, restrain step-length establish comparatively large then can cause image filtering after distortion larger.Initial rectangular window length and width are set to by the present embodiment respectively with the convergence step-length of rectangular window length and width is set to respectively with
Step 4, carry out two-dimentional inverse Fourier transform to the view data of cepstrum domain two-dimentional after filtering, formula is as follows:
g ` ( x , y ) = 1 N 1 N 2 Σ k 1 = 0 N 1 - 1 Σ k 2 = 0 N 2 - 1 G ` ( k 1 , k 2 ) exp { + j 2 π ( k 1 x N 1 + k 2 y N 2 ) } Formula (8)
In formula, the view data that g` (x, y) is two-dimentional cepstrum domain homomorphism numeric field data after two-dimentional inverse Fourier transform.
Step 5, carry out exponential transform obtain filtered view data I` (x, y) to the data in homomorphism territory after filtering, formula is as follows:
I` (x, y)=exp (g` (x, y)) formula (9).
The technical scheme utilizing the present embodiment to provide to the filter effect of Noise SAR image and utilize traditional based on Contrast on effect after frequency domain filtering as shown in Fig. 2-a to 2-f, Fig. 2-a is original noise-free picture, 2-b is Noise SAR image, 2-c is the SAR data of two-dimentional cepstrum domain, 2-d for two-dimentional cepstrum domain add rectangular window carry out filtering after SAR data, 2-e utilizes traditional filtered SAR image of frequency domain filtering method, and 2-f carries out SAR image after filtering for the technical scheme utilizing the present embodiment to provide.Inhibition is compared by picture appraisal parameter, comprises the variance of image, equivalent number, dynamic range, similarity, peak value noise acoustic ratio, entropy, as shown in table 2.Find that the technical scheme that provides of the present embodiment more effectively inhibits speckle noise compared with traditional filtering algorithm based on frequency domain by contrast.
Table 2 compares with filter effect of the present invention based on frequency domain filtering
In sum, SAR data is transformed to homomorphism territory by utilizing isomorphic transformation by the technical scheme that the present embodiment provides, the speckle noise of multiplicative is transformed into additive noise, again homomorphism numeric field data is transformed to two-dimentional cepstrum domain, effectively the radar signal of low frequency and the speckle noise of high frequency are made a distinction at two-dimentional cepstrum domain, and utilize when filtering entropy to carry out adaptivity filtering, restrained effectively the speckle noise of SAR, improve the resolution of image, improve picture quality.
Obviously; the above embodiment of the present invention is only for example of the present invention is clearly described; and be not the restriction to embodiments of the present invention; for those of ordinary skill in the field; can also make other changes in different forms on the basis of the above description; here cannot give exhaustive to all embodiments, every belong to technical scheme of the present invention the apparent change of extending out or variation be still in the row of protection scope of the present invention.

Claims (9)

1. for the synthesis of an adaptive filter method for aperture radar SAR image, it is characterized in that, the method comprises the steps:
S1, carry out log-transformation to containing the SAR image data of speckle noise, obtain the SAR image data of homomorphism territory containing speckle noise;
S2, to described homomorphism territory containing the SAR image data of speckle noise carry out orientation to distance to two-dimensional Fourier transform, obtain the SAR image data of two-dimentional cepstrum domain containing speckle noise;
S3, utilizing two-dimensional rectangle window function to carry out filtering to described two-dimentional cepstrum domain containing the SAR image data of speckle noise, obtaining the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing;
S4, to described two-dimentional cepstrum domain speckle noise through suppress SAR image data carry out orientation to distance to two-dimentional inverse Fourier transform, obtain homomorphism territory speckle noise through suppress SAR image data;
S5, to described homomorphism territory speckle noise through suppress SAR image data carry out exponential transform, obtain speckle noise through suppress SAR image data.
2. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 1, is characterized in that, described step S3 comprises following sub-step further:
S3.1, set the length of rectangular window and the initial value of width in two-dimensional rectangle window function respectively at two-dimentional cepstrum domain, and set the length of rectangular window and the convergence step-length of width in two-dimensional rectangle window function respectively;
S3.2, rectangular window function is utilized to carry out filtering to described two-dimentional cepstrum domain containing the SAR image data of speckle noise and the entropy of view data after calculation of filtered;
S3.3, reduce length and the width of rectangular window in two-dimensional rectangle window function respectively according to the convergence step-length of the length of rectangular window in two-dimensional rectangle window function and width;
S3.4, iterative step S3.2 and step S3.3, until the entropy of filtered image data no longer reduces, obtain the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing.
3. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 2, it is characterized in that, in described step S3.1 in two-dimensional rectangle window function the length of rectangular window and the initial value of width be set as respectively orientation in step S2 to the dimension of Fourier transform 1/2nd and dimension from distance to Fourier transform 1/2nd.
4. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 2, it is characterized in that, in described step S3.1 in two-dimensional rectangle window function the length of rectangular window and the convergence step-length of width be set as respectively orientation in step S2 to the dimension of Fourier transform 1/10th and dimension from distance to Fourier transform 1/10th.
5. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 1, is characterized in that, in step S2 to described homomorphism territory containing the SAR image data of speckle noise carry out orientation to distance to the formula of two-dimensional Fourier transform be:
G ( k 1 , k 2 ) = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ I ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } = Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ S ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) } + Σ x = 0 N 1 - 1 Σ y = 0 N 2 - 1 { log 10 [ w ( x , y ) ] } exp { - j 2 π ( k 1 x N 1 + k 2 y N 2 ) }
In formula, x represent orientation to, y represent distance to, I (x, y) is the SAR image data containing speckle noise, log 10(I (x, y)), for homomorphism territory is containing the SAR image data of speckle noise, S (x, y) is not containing the SAR image data of speckle noise, log 10(S (x, y)), for homomorphism territory is not containing the SAR image data of speckle noise, w (x, y) is speckle noise data, log 10(w (x, y)) is homomorphism territory speckle noise data, and j represents imaginary number, k 1for with orientation to orientation corresponding to x to cepstrum variable, k 2for with distance to distance corresponding to y to cepstrum variable, N 1for orientation is to dimension, the N of Fourier transform 2for distance is to the dimension of Fourier transform, G (k 1, k 2) for two-dimentional cepstrum domain is containing the SAR image data of speckle noise.
6. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 5, is characterized in that, the formula utilizing two-dimensional rectangle window function to carry out filtering to described two-dimentional cepstrum domain containing the SAR image data of speckle noise in step S3 is as follows:
G`(k 1,k 2)＝H(k 1,k 2)G(k 1,k 2)
In formula, G` (k 1, k 2) be the SAR image data of two-dimentional cepstrum domain speckle noise through suppressing, H (k 1, k 2) be two-dimensional rectangle window function.
7. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 6, is characterized in that, described two-dimensional rectangle window function H (k 1, k 2) function formula as follows:
H = ( k 1 , k 2 ) = rect ( k 1 l 1 ) rect ( k 2 l 2 )
In formula, l 1for the length of rectangular window in two-dimensional rectangle window function, l 2for the width of rectangular window in two-dimensional rectangle window function, rect represents rectangular function.
8. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 6, it is characterized in that, in step S4 to the SAR image data of described two-dimentional cepstrum domain speckle noise through suppressing carry out orientation to distance to the formula of two-dimentional inverse Fourier transform be:
g ` ( x , y ) = 1 N 1 N 2 Σ k 1 = 0 N 1 - 1 Σ k 2 = 0 N 2 - 1 G ` ( k 1 , k 2 ) exp { + j 2 π ( k 1 x N 1 + k 2 y N 2 ) }
In formula, g` (x, y) is the SAR image data of homomorphism territory speckle noise through suppressing.
9. the adaptive filter method for the synthesis of aperture radar SAR image according to claim 8, is characterized in that, in step S5 to the formula that the SAR image data of described homomorphism territory speckle noise through suppressing carry out exponential transform is:
I`(x,y)＝exp(g`(x,y))
In formula, I` (x, y) is the SAR image data of speckle noise through suppressing.
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