CN106251368A - SAR image based on BEMD and the fusion method of multispectral image - Google Patents

Abstract

The present invention a kind of SAR image and the fusion method of multispectral image, including: multispectral image is carried out IHS conversion and obtains I, H, S component；SAR image and I component are carried out respectively BEMD conversion and obtains IMF component and the residual components of SAR image and I component；Adjust SAR image and the IMF component of I component and residual components, make the IMF component number of the two keep consistent, and unnecessary IMF component is added corresponding residual components；SAR image after adjusting respectively and IMF component and the IMF component of I component, and residual components merges with residual components；BEMD inverse transformation is carried out, the I component after being merged according to fusion results；I component, H component and S component after merging is carried out IHS inverse transformation, the image after being merged.The SAR image based on BEMD of the present invention and the fusion method of multispectral image save preferable texture information, it is possible to the concrete segmentation for similar atural object provides Reliable guarantee, improves non-linear, the analysis of non-stationary signal and disposal ability.

Description

SAR image based on BEMD and the fusion method of multispectral image

Technical field

The present invention relates to image processing field, particularly relate to melting of a kind of SAR image based on BEMD and multispectral image Conjunction method.

Background technology

Along with the fast development of sensor technology, remote sensing technology etc., multi-platform, stage construction, multidate, multisensor, many The remote sensing image of spectrum and multiresolution constitutes the multi-source remote sensing information of multizone.Different sensors has different imagings Mechanism and work in different wave-length coverages, the image therefore obtained often reflects the feature of atural object different aspect.By list The information that one sensor is provided is probably the most comprehensive, inconsistent, the most inaccurate.The most multiple in order to more effectively utilize Miscellaneous Multi-source Remote Sensing Image Information, associated image fusion technology arises at the historic moment.

Synthetic aperture radar (Synthetic Aperture Radar, SAR) is a kind of microwave remote sensor, and it is by actively Launch electromagnetic wave and receive the electromagnetic wave information of return and realize remotely sensed image.For optical pickocff, synthetic aperture thunder Reaching and have round-the-clock, imaging capability round-the-clock, high-resolution, and its operating distance far, areas imaging is wide, penetration capacity By force, solve optical remote sensing sensor and affected problem by time and weather.

At present, conventional fusion method has: IHS conversion, PCA conversion, Brovey conversion and wavelet transformation, wherein, and IHS Conversion, PCA conversion and Brovey conversion normally result in the more serious spectrum distortion of ratio, and wavelet transformation then solves spectrum and turns round Bent problem.But, said method is mainly used in the fusion of multispectral image and panchromatic image, in this paper to optics shadow During as merging with High-resolution SAR Images, use said method can lose a large amount of texture information, trickle atural object is being carried out Classification has great difficulty when extracting.

Below, the prior art to above-mentioned Remote Sensing Image Fusion field does a more detailed description, in order to more preferably Ground understands the present invention.

Traditional Remote Sensing Image Fusion typically uses optics panchromatic image to merge with multispectral image, traditional fusion Method includes: IHS conversion, principal component transform (PCA), ratio fusion method, PCA (Karhunen-Loeve transformation), Weighted Fusion method, Wavelet Transform etc..

As a example by IHS converts: the different-waveband remotely-sensed data that will be obtained by modes such as optics, thermal infrared and radars (microwave) One RGB color being described object color attribute of synthesis transforms to brightness (Intensity), colourity H (Hue), saturation S (Saturation) describes the IHS color space of image.

The blending algorithm of IHS conversion is as follows:

Just becoming formula:

$\left[\begin{array}{c}I\\ v_1\\ v_2\end{array}\right]=\left[\begin{array}{ccc}\frac{1}{\sqrt{3}}& \frac{1}{\sqrt{3}}& \frac{1}{\sqrt{3}}\\ \frac{1}{\sqrt{6}}& \frac{1}{\sqrt{6}}& -\frac{2}{\sqrt{6}}\\ \frac{1}{\sqrt{2}}& \frac{1}{\sqrt{2}}& 0\end{array}\right]*\left[\begin{array}{c}R\\ G\\ B\end{array}\right]$

$S=\sqrt{v_1^2+v_2^2}$

H=arctg (v₁/v₂)

In formula: I represents that brightness, H represent that colourity, S represent that saturation, v1, v2 are to calculate the middle change that I, H introduce Amount.

The anti-formula that changes:

$\left[\begin{array}{c}R\\ G\\ B\end{array}\right]=\left[\begin{array}{ccc}\frac{1}{\sqrt{3}}& \frac{1}{\sqrt{6}}& \frac{1}{\sqrt{2}}\\ \frac{1}{\sqrt{3}}& \frac{1}{\sqrt{6}}& -\frac{1}{\sqrt{2}}\\ \frac{1}{\sqrt{3}}& \frac{1}{\sqrt{6}}& 0\end{array}\right]*\left[\begin{array}{c}I\\ v_1\\ v_2\end{array}\right]$

As a example by wavelet transformation: the process of Wavelet Transform Fusion is as follows:

Wavelet transformation is defined as:

Transformation kernel function is:

Wherein,It is a wavelet, also known as morther wavelet, or wavelet basis, it is centered by t=0 is Band pass function, and time domain average value

Wavelet transformation is, processes low-frequency information with space large scale, with space little scale processing high-frequency information.

At present, the multiscale analysis method used in the fusion method of SAR image and optical image specifically include that two dimension from Dissipate wavelet transformation, shift-invariant spaces and represent anisotropic warp wavelet etc..Those skilled in the art should Working as understanding, a kind of linear transformation of wavelet transformation, to non-linear, the disposal ability of non-stationary signal is limited；And, Wavelet transformation is non-adaptive, and its syncretizing effect depends on the selection of wavelet basis.

Accordingly, it would be desirable to a kind of method carrying out High-resolution SAR Images and optical image merging, the method can overcome Existing method is processing defect the most weak on non-linear, non-stationary signal, and can keep in multi-source image simultaneously Spectral information, marginal information and texture information.

The meaning of the abbreviation of the Partial key term in this specification is illustrated at this, including: the one-dimensional empirical modal of EMD Decompose (Empirical Mode Decomposition, EMD)；Two-dimensional empirical mode decomposition (BidimensionalEmpirical Mode Decomposition,BEMD)；Intrinsic mode functions (Intrinsic Mode Function,IMF)；Synthetic aperture radar ((SyntheticApertureRadar, SAR).

Summary of the invention

It is an object of the invention to provide a kind of synthetic aperture radar SAR image that can overcome drawbacks described above and multispectral shadow The fusion method of picture.

In first aspect, the invention provides the fusion method of a kind of synthetic aperture radar SAR image and multispectral image, It is characterized in that: multispectral image is carried out IHS conversion, obtain the I component of described multispectral image, H component and S component；Right Described SAR image and described I component carry out two-dimensional empirical mode decomposition BEMD conversion respectively, obtain the intrinsic of described SAR image Modular function IMF component and residual components, and the IMF component of described I component and residual components；The IMF of described SAR image is divided Measure and residual components, and the IMF component of described I component and residual components are adjusted, and make the IMF component of described SAR image Keep consistent with the IMF component number of described I component, and unnecessary IMF component is added corresponding residual components；Respectively by institute The residual components stating the SAR image after the IMF component of the SAR image after adjustment and the IMF component of I component, and adjustment divides with I The residual components of amount merges；BEMD inverse transformation is carried out, the I component after being merged according to fusion results；To the I after merging Component, described H component and described S component carry out IHS inverse transformation, the image after being merged.

Preferably, the step of described BEMD conversion includes: the image converting pending BEMD initializes；At the beginning of identification The extreme point in image after beginningization；In the case of described extreme point meets predetermined threshold, by described extreme point is carried out Matching, obtains the average envelope face of image；The local trend of image is extracted according to described average envelope face；At described local trend In the case of meeting predetermined IMF condition, described local trend is judged to IMF component；Remnants are calculated according to described IMF component Component；In the case of described residual components meets predetermined monotony condition, described residual components is judged to that final remnants divide Amount.

Preferably, in the case of described local trend is unsatisfactory for IMF decision condition, replace initial with described local trend Image after change, continually looks for extreme point therein；In the case of described residual components is unsatisfactory for monotony condition, with described residual Remaining component replaces the image after initializing, and continually looks for extreme point therein.

Preferably, described IMF decision condition is according between the extreme point in the image identifying extreme point wherein and zero point Relation and described average envelope face value determine；Described monotony condition passes through two IMF component meters in succession judging out Obtain.

Preferably, before multispectral image is carried out the step of IHS conversion, also include: described SAR image is gone Make an uproar；The SAR image after denoising and the pixel resolution of described multispectral image is unified by resampling；After resampling SAR image and multispectral image carry out Image registration.

Preferably, before the step of described fusion, also include: the IMF component of the SAR image after described adjustment is divided with I The IMF component of amount carries out Laplce's high-pass filtering, and the remnants to the residual components of the SAR image after adjusting with I component Component carries out Laplce's low-pass filtering；Result based on described filtering calculates the IMF component in described SAR image and residual respectively The weight of each pixel in remaining component；Wherein, described fusion is carried out based on described weight.

The SAR image based on BEMD of the present invention and the fusion method of multispectral image save preferable texture information, Reliable guarantee can be provided for the concrete segmentation of similar atural object, improve non-linear, the analysis of non-stationary signal and process Ability.

Accompanying drawing explanation

Fig. 1 is the flow chart of the SAR based on BEMD according to the embodiment of the present invention and the fusion method of multispectral image；

Fig. 2 is the flow chart of the BEMD conversion in Fig. 1；

Fig. 3 is the fusion results figure of the multi-source Remote Sensing Images of Guilin Area based on wavelet transformation；

Fig. 4 is the fusion results figure of the multi-source Remote Sensing Images of the Guilin Area of fusion method based on the present invention.

Detailed description of the invention

Below by drawings and Examples, technical scheme is described in further detail.

The most weak lacking on non-linear, non-stationary signal is being processed for existing Remote Sensing Image Fusion alternative approach Falling into, the present invention proposes a kind of new Remote Sensing Image Fusion alternative approach.BEMD conversion be applicable to non-linear, non-stationary signal point Analysis, has relatively high s/n ratio；It addition, the time first reading feature of BEMD basis signal self realizes signal decomposition, finally merge effect Fruit is independent of the selection of any basic function, has adaptivity completely.Utilize BEMD alternative approach, present invention achieves SAR Image and the fusion of high score optical image.

First, image fusing method of the present invention is broadly described as follows several step.

1) the object image of multi-source RS Images Fusion is carried out pretreatment.

For example, it is possible to choose the SAR image obtained with TerraSAR-X satellite and the multispectral image of GF-1 camera acquisition Carry out visual fusion.Preferably, for ensureing syncretizing effect, the most first two kinds of image datas are carried out geographical calibration, geometric correction, The pretreatment such as Image registration, filtering and noise reduction.Owing to two kinds of images have different spatial resolution, before carrying out Image registration The pixel resolution of image need to be unified；Further, since SAR image exists angle of incidence when obtaining, need to disappear in preprocessing process Except ghost image.

2) for problems such as the calculating circulations during visual fusion, the big of image pixel and imaging window is reasonably chosen Little.Image pixel size can choose the multiple of 8, is preferably optimal with square；And image is unsuitable excessive, such as can select Taking imaging window size is 4000*4000.

3) multispectral image and SAR image are carried out BEMD decomposition.

Multispectral image contains three wave bands R, G, B, and IHS color space three-component has relative independentability, it is possible to more Good embodiment color information.Therefore, multispectral image is first carried out IHS conversion, after carry out BEMD decomposition, i.e. to its three wave bands Decompose respectively.In an experiment, can define decomposition and obtain four layers of component, respectively three IMF components and remnants divide Amount.Oneth IMF component is high-frequency information, second and three-component frequency information reduce successively, residual components is the brightest Degree information.

SAR image only one of which wave band, i.e. gray scale wave band, then also the gray scale wave band of SAR image is carried out BEMD decomposition.

4) will decompose after SAR image greyscale wave band with decomposition after multispectral image I component merge, then with H, The merging of S component is reconverted into R, G, B, finally obtains fusion evaluation.

Below, the fusion side based on BEMD high-resolution SAR image Yu optical image according to the present invention is described in detail Method.

Fig. 1 is the flow process of the SAR image based on BEMD according to the embodiment of the present invention and the fusion method of multispectral image Figure.

The first step: Yunnan snub-nosed monkey, its process mainly includes image resampling, SAR image denoising, Image registration.

It is possible, firstly, to by the pixel resolution of the unified two width images of down-sampling.

Secondly as SAR image is the most affected by noise, thus cause non-linear, the non-stationary signal of image empty with image Between resolution improve and further obvious, intrinsic noise is the most prominent.Accordingly, it would be desirable to first to it before SAR image is sampled Carry out denoising, such as, can use improvement Goldstein filtering that SAR image is carried out noise reduction process.

Finally, for the SAR image after denoising, sampling and the multispectral image after sampling, gather corresponding image points to carrying out Image registration.

Second step: SAR image is merged with multispectral image, its concrete operation step is as follows:

1, multispectral image is carried out IHS conversion (i.e. color space conversion in Fig. 1), obtain the I of multispectral image, H, S component.

$\left[\begin{array}{c}I\\ v_1\\ v_2\end{array}\right]=\left[\begin{array}{ccc}\frac{1}{\sqrt{3}}& \frac{1}{\sqrt{3}}& \frac{1}{\sqrt{3}}\\ \frac{1}{\sqrt{6}}& \frac{1}{\sqrt{6}}& -\frac{2}{\sqrt{6}}\\ \frac{1}{\sqrt{2}}& \frac{1}{\sqrt{2}}& 0\end{array}\right]*\left[\begin{array}{c}R\\ G\\ B\end{array}\right]$

$S=\sqrt{v_1^2+v_2^2}$

H=arctg (v₁/v₂)

Note: v1, v2 are intermediate variable.

2, the multispectral image I component after pretreated SAR image and conversion is carried out BEMD conversion respectively.

Converted by BEMD respectively, obtain IMF component and the residual components R of SAR image, and obtain multispectral image IMF component and residual components R.After BEMD decomposes, SAR image is represented byMultispectral shadow As I component is represented byWherein, I, R are respectively IMF component and residual components；M, N are respectively The number of SAR and the decomposable IMF of I component of multispectral image.

3, the image decomposition amount of SAR image and multispectral image is processed, make the two have identical Decomposition order.

Owing to BEMD has a complete adaptivity, the I component of SAR image and multispectral image is obtained after being decomposed by BEMD IMF number may be different, thus cause in follow-up fusion process inconsistent.Accordingly, it would be desirable to the decomposition amount to image Processing, the Decomposition order making image to be fused is consistent.Specifically, can set in BEMD converts decompose after will obtain IMF number so that the IMF number that two kinds of images finally give is identical.Such as, if n=min{M, N}, as a example by n=M, how light IMFs component after n-th IMF of the I component of spectrum image will be added in residual components so that it is IMF number is n.This Time, the I component of multispectral image can be expressed as:

$F^{MI}=\underset{n=1}{\overset{N}{\Σ}}{I}_n^{MI}+R_N^{MI}$

Wherein,

4, the component obtained SAR image and multispectral image by BEMD conversion carries out Laplce's filtering, with detection Marginal information in image.Such as, the IMF component of SAR image and multispectral image is carried out Laplce's high-pass filtering, to two The residual components of person carries out Laplce's low-pass filtering.Marginal information in image mainly corresponding high-frequency information, i.e. passes through BEMD The IMF component respectively obtained, correspondingly, low-frequency information therein is residual components.

5, whether the pixel window determined based on Laplace operator, smooth in detection window region.By detection, it is judged that The information of same frequency whether is obtained after previous step filtering.As being judged as smoothing, then show that high-pass filtering obtains is all high Frequently information, what low-pass filtering obtained is all low-frequency information.In other words, smooth show filtering after the information that obtains do not have in frequency Jumping characteristic difference, does not i.e. have edge.

6, in the case of judging that pixel window inner region is smooth, represent that frequency information is same or similar, then deducibility picture It is same atural object in element window, then calculate its average weight；Otherwise need to calculate weight respectively.For example, it is possible to according to Fusion rule based on provincial characteristics calculates the weight of each pixel in each component of SAR image, and by the IMF component of SAR image α it is denoted as respectively with the weight of residual components_n、β。

7, by IMF componentAnd residual componentsCarrying out the fusion of different scale respectively, it merges public affairs Formula is as follows:

$I_n^{fuse}={\mathrm{\α}}_n{I}_n^{SF}+(1-{\mathrm{\α}}_n)I_n^{MI}$

R^fuse=βR^SF+(1-β)R^MI

6, BEMD inverse transformation is carried out, using fusion results as new I component I^fuse, wherein inverse transformation formula is as follows:

$I^{fuse}=\underset{k=1}{\overset{n}{\Σ}}{I}_k^{fuse}+R^{fuse}$

7, by new I component I^fuseColor space inverse transformation is carried out with H, S component of multispectral image, will I^fuseH^MS^M Rgb space is changed in inversion, the image after being merged.

Fig. 2 is the flow chart of the BEMD conversion in Fig. 1.

In step 201, the image converting pending BEMD initializes.

In step 202, identify the extreme point of the image after initializing, specifically, i.e. find its all of local maximum Point and minimum point.

In step 203, it is judged that whether the number of extreme point meets predetermined condition.If it is satisfied, then flow process proceeds to 204； Otherwise flow process proceeds to step 207.

In step 204, select maximum point and the minimum point of effective interpolation algorithm fitted signal respectively, obtain up and down Enveloping surface, and it is calculated average envelope face.

In step 205, extract the local trend of image according to average envelope face；

In step 206, it is judged that whether this local trend meets IMF condition.If meeting, then flow process proceeds to step 207；No Then, replacing the initialized image in step 202 with this local trend, flow process returns to step 202.

IMF decision condition is:

1) for whole data set, | extreme point-zero point |≤1；

2) for any point on data set, the average envelope face amount that local maximum and local minimum determine is zero.

In step 207, this local trend is set as IMF component.

In step 208, calculate residual components according to this IMF component.

In step 209, it is judged that in step 207, whether calculated residual components meets monotony condition.As met, then flow Journey terminates, and this residual components is judged to the residual components finally exported；At the beginning of otherwise replacing in step 202 with this residual components Beginningization image, flow process returns to step 202.

Whether dull residual components criterion be:

1) any IMF is not comprised；Or

2) residual components be less than SD, 0.2 < SD < 0.3,

Generally, SD is arranged in the range of 0.2-0.3, and i.e. when SD meets 0.2 ＜ SD ＜ 0.3, screening process terminates.

Fig. 3 is the fusion results figure of the multi-source Remote Sensing Images of Guilin Area based on wavelet transformation；Fig. 4 is based on the present invention The fusion results figure of multi-source Remote Sensing Images of Guilin Area of fusion method.Can substantially be seen by the comparison of Fig. 3 and Fig. 4 Go out, save preferable texture information according to the fusion method of the present invention, it is possible to the concrete segmentation offer for similar atural object can By ensureing, improve non-linear, the analysis of non-stationary signal and disposal ability.

Multi-source Remote Sensing Images is merged, as the basis of classification of remote-sensing images by the present invention based on BEMD conversion, it is possible to Ensure process linear or non-linear, steadily or while non-stationary signal, it is ensured that the light that multi-source Remote Sensing Images is comprised Spectrum information, marginal information and texture information are not lost.Tradition SAR mainly uses two-dimensional discrete little with optical image fusion method The linear transformation such as wave conversion, translation invariant wavelet, these methods abandon non-linear and non-stationary letter to a great extent Number process.The integration program that the present invention provides is more suitable for non-linear, the analysis of non-stationary signal, has higher noise Ratio.It addition, BEMD conversion is better than wavelet transformation and is that it is different from wavelet transformation and depends on wavelet basis when to signal processing Selecting, it is to rely on signal its temporal scale feature to realize signal decomposition, has complete adaptivity.

Professional should further appreciate that, each example described in conjunction with the embodiments described herein Unit and algorithm steps, it is possible to electronic hardware, computer software or the two be implemented in combination in, hard in order to clearly demonstrate Part and the interchangeability of software, the most generally describe composition and the step of each example according to function. These functions perform with hardware or software mode actually, depend on application-specific and the design constraint of technical scheme. Professional and technical personnel can use different methods to realize described function to each specifically should being used for, but this realization It is not considered that it is beyond the scope of this invention.

The method described in conjunction with the embodiments described herein or the step of algorithm can use hardware, processor to perform Software module, or the combination of the two implements.Software module can be placed in random access memory (RAM), internal memory, read only memory (ROM), electrically programmable ROM, electrically erasable ROM, depositor, hard disk, moveable magnetic disc, CD-ROM or technical field In any other form of storage medium well known in.

Above-described detailed description of the invention, has been carried out the purpose of the present invention, technical scheme and beneficial effect further Describe in detail.Be it should be understood that the detailed description of the invention that the foregoing is only the present invention, be not intended to limit the present invention Protection domain.All within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. done, all should comprise Within protection scope of the present invention.

Claims (6)

1. a synthetic aperture radar SAR image based on BEMD and the fusion method of multispectral image, it is characterised in that:

Multispectral image is carried out IHS conversion, obtains the I component of described multispectral image, H component and S component；

Described SAR image and described I component are carried out two-dimensional empirical mode decomposition BEMD conversion respectively, obtains described SAR image Intrinsic mode functions IMF component and residual components, and the IMF component of described I component and residual components；

IMF component and residual components to described SAR image, and the IMF component of described I component and residual components adjust Whole, make the IMF component of described SAR image keep consistent with the IMF component number of described I component, and unnecessary IMF component is added Enter the residual components of correspondence；

Respectively by the IMF component of the IMF component of the SAR image after described adjustment Yu I component, and the SAR image after adjustment Residual components merges with the residual components of I component；

BEMD inverse transformation is carried out, the I component after being merged according to fusion results；

I component, described H component and described S component after merging is carried out IHS inverse transformation, the image after being merged.

Synthetic aperture radar SAR image based on BEMD the most according to claim 1 and the fusion method of multispectral image, it is special Levying and be, the step of described BEMD conversion includes:

The image converting pending BEMD initializes；

Identify the extreme point in the image after initializing；

In the case of described extreme point meets predetermined threshold, by described extreme point is fitted, obtain the average of image Enveloping surface；

The local trend of image is extracted according to described average envelope face；

In the case of described local trend meets predetermined IMF condition, described local trend is judged to IMF component；

Residual components is calculated according to described IMF component；

In the case of described residual components meets predetermined monotony condition, described residual components is judged to that final remnants divide Amount.

Synthetic aperture radar SAR image based on BEMD the most according to claim 2 and the fusion method of multispectral image, it is special Levy and be:

In the case of described local trend is unsatisfactory for IMF decision condition, replace the image after initializing with described local trend, Continually look for extreme point therein；

In the case of described residual components is unsatisfactory for monotony condition, replaces the image after initializing with described residual components, continue Continuous searching extreme point therein.

Synthetic aperture radar SAR image based on BEMD the most according to claim 2 and the fusion method of multispectral image, it is special Levy and be:

Described IMF decision condition is according to the relation between the extreme point in the image identifying extreme point wherein and zero point and institute The value stating average envelope face determines；

Described monotony condition is calculated by two IMF components in succession judging out.

Synthetic aperture radar SAR image based on BEMD the most according to claim 1 and the fusion method of multispectral image, it is special Levy and be, before multispectral image is carried out the step of IHS conversion, also include:

Described SAR image is carried out denoising；

The SAR image after denoising and the pixel resolution of described multispectral image is unified by resampling；

SAR image after resampling and multispectral image are carried out Image registration.

Synthetic aperture radar SAR image based on BEMD the most according to claim 1 and the fusion method of multispectral image, it is special Levy and be, before the step of described fusion, also include:

The IMF component of the SAR image after described adjustment and the IMF component of I component are carried out Laplce's high-pass filtering, and right The residual components of the SAR image after adjustment and the residual components of I component carry out Laplce's low-pass filtering；

Result based on described filtering calculates the weight of each pixel in the IMF component in described SAR image and residual components respectively；

Wherein, described fusion is carried out based on described weight.