CN106408532B - Synthetic aperture radar SAR image denoising method based on the estimation of shearing wave field parameter - Google Patents
Synthetic aperture radar SAR image denoising method based on the estimation of shearing wave field parameter Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000010008 shearing Methods 0.000 title claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 11
- 230000009466 transformation Effects 0.000 claims description 9
- 238000000354 decomposition reaction Methods 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000011084 recovery Methods 0.000 claims description 3
- 230000001427 coherent effect Effects 0.000 abstract description 9
- 238000003018 immunoassay Methods 0.000 abstract description 2
- 230000005764 inhibitory process Effects 0.000 abstract description 2
- 238000005191 phase separation Methods 0.000 abstract description 2
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- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The present invention relates to a kind of synthetic aperture radar SAR image denoising methods based on the estimation of shearing wave field parameter to be distributed the statistical property of description speckle noise with Rayleigh (Rayleigh) in the phase separation immunoassay processing of SAR image.Since the mathematic(al) representation of laplacian distribution model is simple, it is commonly available the analytic solutions of estimation in conjunction with bayesian theory, for representing the shearing wave coefficient of back scattering component, then indicates the probability density function of shearing wave coefficient using laplacian distribution.The experimental results showed that the denoising method based on shearing wave parameter Estimation has apparent inhibition to the coherent speckle noise in SAR image, and preferably maintain the Edge texture information in image.
Description
Technical field
The SAR image denoising method that the invention belongs to be estimated based on shearing wave field parameter is related to a kind of based on shearing wave zone
The synthetic aperture radar SAR image denoising method of parameter Estimation, can be applied to Single-Look SAR Image, removes the multiplying property of SAR image
Coherent speckle noise.
Background technique
SAR (synthetic aperture radar (Synthetic Aperture Radar, abbreviation SAR)) is a kind of high-resolution imaging thunder
It reaches, belongs to active remote sensing system, there are round-the-clock, round-the-clock, multipolarization, multi-angle of view, more angle of depression data retrieval capabilities and right
The penetration performance of some atural objects is compared with other sensors, and more details can be presented, can be accurately determined the big of target area
It is small, it can better discriminate between the characteristic of adjacent objects, however the coherent speckle noise that SAR image is intrinsic, seriously reduce SAR image
Degree can be interpreted, the applications such as succeeding target detection, classification, identification and information extraction are affected.Therefore, to SAR image coherent spot
The research of suppressing method just becomes a part particularly important in SAR image processing technique, and elementary object is to inhibit image
Under the premise of homogeneous area speckle noise is horizontal, the detailed information such as image border and texture are kept.
Since SAR image speckle noise has the characteristics that multiplying property, relative to additive noise, spot inhibits more difficult.More rulers
Spending geometrical analysis is " second of the small echo tide " risen in the world in recent years, overcomes small echo and is unable to rarefaction representation higher-dimension spy
The shortcomings that sign, is increasingly taken seriously.The method for being absorbed in SAR image denoising is quite a few, such as SAR based on bent wave Curvelet
Image de-noising method, denoising method based on Contourlet etc..However, in subsequent research, Qu Bo and profile
Wave has been demonstrated do not have translation invariance, so the application in image de-noising method is restricted.Shear wave conversion due to
Its stability, directional sensitivity, translation invariance and optimal sparse approximation, the advantages that being easily achieved, are in numerous more rulers
Show one's talent in degree geometrical analysis tool, huge potentiality are shown in terms of the edge extracting of image and denoising.But at present
Gaussian noise removal is similar to based on shearing the algorithm of wave zone SAR image denoising, using coherent speckle noise after logarithm process
Transformation coefficient is either divided into the method that texture, edge and smooth area three classes are handled by method processing, is not accounted for mostly
The model of noise.
Summary of the invention
Technical problems to be solved
In order to avoid the shortcomings of the prior art, the present invention proposes a kind of synthesis hole based on the estimation of shearing wave field parameter
Diameter radar SAR image denoising method.
Technical solution
A kind of synthetic aperture radar SAR image denoising method based on the estimation of shearing wave field parameter, it is characterised in that step
It is as follows:
Step 1, shearing wave Shearlet are decomposed: being done shearing Wave Decomposition to the SAR image of the speckle noise Han multiplying property, divided
Coefficient S after solution, indicates low-frequency approximation coefficient with L (S), indicates high frequency detail coefficient with Y (S)；
Step 2, parameter Estimation:
Utilize the attenuation parameter α of low-frequency approximation coefficient L (S) estimation noise variance σ and rayleigh distributed:
The edge standard deviation sigma of each coefficient is estimated using high frequency detail coefficient Y (S)s(s), local auto-adaptive threshold value λ is calculated
Soft-threshold processing is done with to current coefficient；
The edge standard deviation sigma of each coefficients(s):
Wherein: N (s) is the neighborhood window centered on current coefficient y (s), and M is coefficient number in window；
Calculate local auto-adaptive threshold value λ:
Soft-threshold processing is done to current coefficient:
Wherein: sign (y) is sign function,
()+It is indicative function,
Step 3, shearing wave inverse transformation reconstruct: to treated, low-frequency approximation coefficient L (S) and high frequency detail coefficient Y (S) is done
Shearing wave inverse transformation, the recovery image after being denoised.
The step 1 carries out shearing wave conversion to the SAR image comprising multiplying property speckle noise, Decomposition order 4, in window
Coefficient number is 3 × 3.
Beneficial effect
A kind of synthetic aperture radar SAR image denoising method based on the estimation of shearing wave field parameter proposed by the present invention,
In the phase separation immunoassay processing of SAR image, the statistical property of description speckle noise is distributed with Rayleigh (Rayleigh).It is general due to drawing
The mathematic(al) representation of Lars distributed model is simple, and the analytic solutions of estimation are commonly available in conjunction with bayesian theory, after representing
To the shearing wave coefficient of scattering component, then the probability density function of shearing wave coefficient is indicated using laplacian distribution.
Shearing wave conversion is a kind of multi-scale geometric analysis (Multiscale Geometric more suitable for image procossing
Analysis, MGA) method, have many advantages, such as stability, directionality, translation invariance and be easily achieved, wherein translation
Invariance makes it more suitable for image denoising.Synthetic aperture radar (SAR) image has very strong coherent speckle noise, how to keep
It is all that the difficult point that SAR image is handled is asked that preferable Speckle reduction effect is obtained on the basis of edge and grain details all the time
One of topic.Based on shearing wave to the optimum linearity approximation capability of high dimensional data, shearing wave conversion is introduced into SAR image denoising, it is right
The target signature for shearing the coefficient combination SAR image of wave conversion is handled.Laplce's mould is used to the signal in SAR image
Type, the rayleigh model that multiplicative noise is used to coherent speckle noise use class to transformation coefficient using Bayes's method for parameter estimation
New shearing wave transformation coefficient is obtained after being similar to the method processing of soft-threshold.Despeckle image is obtained after reconstruct.The experimental results showed that
Denoising method based on shearing wave parameter Estimation has apparent inhibition to the coherent speckle noise in SAR image, and preferably keeps
Edge texture information in image.
Detailed description of the invention
Fig. 1: the basic flow chart of the method for the present invention
Fig. 2: true SAR image denoising result:
(a) SAR image, (b) mean filter, (c) median filtering, (d) LEE is filtered, (e) Wiener filtering, and (f) small echo is filtered
Wave, (g) bent wave filtering, (h) denoising result of this method
Specific embodiment
Now in conjunction with embodiment, attached drawing, the invention will be further described:
Hardware environment for implementation is: Intel (R) core (TM) i5-3230M computer, 4GB memory, operation it is soft
Part environment is: Matlab7.0 and Windows 8.Method proposed by the present invention is realized with Matlab programming language.Image
Data simulate SAR image and a width true picture SAR image using the method for multiplicative noise is added on natural image.
Present invention specific implementation is as follows:
Step 1: shearing wave (Shearlet) decomposes: doing shearing Wave Decomposition to the SAR image of the speckle noise Han multiplying property, obtains
Coefficient S after decomposition, indicates low-frequency approximation coefficient with L (S), indicates high frequency detail coefficient with Y (S)；
Step 2: parameter Estimation
1) the attenuation parameter α of low-frequency approximation coefficient L (S) estimation noise variance σ and rayleigh distributed is utilized；
2) high frequency detail coefficient processing: to high frequency detail coefficient Y (S):
A) estimate the edge standard deviation sigma of each coefficients(s):
Wherein N (s) is the neighborhood window centered on current coefficient y (s), and M is coefficient number in window.
B) local auto-adaptive threshold value λ is calculated:
C) soft-threshold processing is done to current coefficient:
Sign (y) is sign function,
()+It is indicative function,
Step 3: shearing wave inverse transformation reconstruct: to treated, low-frequency approximation coefficient L (S) and high frequency detail coefficient Y (S) is done
Shearing wave inverse transformation, the recovery image after being denoised.
For simulating SAR image obtained by natural image addition multiplicative noise, by the resulting denoising result of the present invention and other
The resulting result of denoising method compares, and it is as shown in table 1 to objectively evaluate result difference.
The different indexs that objectively evaluate have different physical significances, using mean value, equivalent number, edge conservation degree, letter
Make an uproar than and Y-PSNR evaluate the effect of speckle noise filtering algorithm.
Edge conservation degree β (edge preservation measure) is defined as:
Wherein Δ S,Be S andPass through the high-pass filtering result of 3 × 3 standard Laplace operators.For ideal side
Edge is kept, and β should be close to 1.
The common counter for evaluating SAR image coherent speckle noise intensity is equivalent number, from table 1 (lena simulates SAR image)
Various denoising evaluation indexes in as can be seen that the Speckle reduction effect of mean filter and median filtering is obviously poor, denoising
Still considerable speckle noise is remained in figure, equivalent number numerical value is smaller, and the effect of LEE filtering is slightly good, but denoises figure
As excessively smooth；Wavelet filtering obviously obscures denoising result figure, and the denoising method based on warp wavelet inhibits big portion
The speckle noise divided, but since warp wavelet is non-translation invariant, so occurring apparent scratch in denoising result figure.
In contrast, this method is preferable on improvement of visual effect based on the denoising method of parameter Estimation.From the denoising result of true SAR image
It is basic it can be concluded that conclusion identical with simulation SAR denoising result from the point of view of figure, and although equivalent view that bent wave filtering method obtains
Number numerical value highest, but there is apparent scratch in filter result image, and in contrast, this method is relatively positive due to parameter Estimation
Really, the edge conservation degree and signal-to-noise ratio numerical value obtained is optimal.
The true SAR image of table 1 denoises Contrast on effect
Claims (2)
1. a kind of synthetic aperture radar SAR image denoising method based on the estimation of shearing wave field parameter, it is characterised in that step is such as
Under:
Step 1, shearing wave Shearlet are decomposed: shearing Wave Decomposition are done to the SAR image of the speckle noise Han multiplying property, after obtaining decomposition
Coefficient S, low-frequency approximation coefficient is indicated with L (S), high frequency detail coefficient is indicated with Y (S)；
Step 2, parameter Estimation:
Utilize the attenuation parameter α of low-frequency approximation coefficient L (S) estimation noise variance σ and rayleigh distributed:
σ=Median | L (S) | }/0.6745
The edge standard deviation sigma of each coefficient S is estimated using high frequency detail coefficient Y (S)s(S), local auto-adaptive threshold value λ and right is calculated
Current coefficient does soft-threshold processing；
The edge standard deviation sigma of each coefficients(S):
Wherein: N (S) is the neighborhood window centered on current coefficient y (S), and M is coefficient number in window；
Calculate local auto-adaptive threshold value λ:
Soft-threshold processing is done to current coefficient:
Wherein: sign (y) is sign function,
()+It is indicative function,
Step 3, shearing wave inverse transformation reconstruct: to treated, low-frequency approximation coefficient L (S) and high frequency detail coefficient Y (S) is sheared
Wave inverse transformation, the recovery image after being denoised.
2. the synthetic aperture radar SAR image denoising method according to claim 1 based on the estimation of shearing wave field parameter, special
Sign is: the step 1 carries out shearing wave conversion to the SAR image comprising multiplying property speckle noise, Decomposition order 4, in window
Coefficient number is 3 × 3.
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| CN112098997B (en) * | 2020-09-18 | 2021-10-15 | 欧必翼太赫兹科技(北京)有限公司 | Three-dimensional holographic imaging security inspection radar image foreign matter detection method |
| CN112927165A (en) * | 2021-03-22 | 2021-06-08 | 重庆邮电大学 | SAR image speckle suppression method based on NSST domain three-dimensional block matching |
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| EP2146315A1 (en) * | 2008-07-16 | 2010-01-20 | Galileian Plus s.r.l. | Method of filtering SAR images from speckle noise and related device. |
| CN102663679A (en) * | 2012-03-02 | 2012-09-12 | 西北工业大学 | Image denoising method based on Shearlet contraction and improved TV model |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| EP2146315A1 (en) * | 2008-07-16 | 2010-01-20 | Galileian Plus s.r.l. | Method of filtering SAR images from speckle noise and related device. |
| CN102663679A (en) * | 2012-03-02 | 2012-09-12 | 西北工业大学 | Image denoising method based on Shearlet contraction and improved TV model |
Non-Patent Citations (2)
| Title |
|---|
| An Improved Image Denoising Algorithm based on Shearlet;Zhiyong Fan et al;《International Journal of Signal Processing.Image Processing and Pattern Recognition》;20130831;第6卷(第4期);第475-483页 * |
| 基于贝叶斯估计的剪切波域局部自适应图像去噪;龚俊亮 等;《液晶与显示》;20131031;第28卷(第5期);第799-804页 * |
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