CN106683064A - Multi-focusing image fusion method based on two-dimensional coupling convolution - Google Patents

Abstract

The invention discloses a multi-focusing image fusion method based on two-dimensional coupling convolution. The method includes the following steps: inputting an image to be fused, and dividing the image into small blocks with the size of M*N through a sliding window technique; and for a single-input and multi-output system model, solving an imaging system F<1><j> and an imaging system F<2><j> in the model through characteristic constant decomposition, and thus selecting clear image blocks. The method of the invention can accurately determine clear image blocks, so that a fused image exhibits great robustness. Moreover, significant clear details of the image can be well fused without artificial traces.

Description

A kind of multi-focus image fusing method based on two dimension coupling convolution

Technical field

The invention belongs to digital image processing techniques field, and in particular to a kind of multi-focus figure based on two dimension coupling convolution As fusion method.

Background technology

With the fast development of information technology, the bloom for obtaining from initial visible light sensor till now of image The different sensors such as spectrum, radar, multispectral, the corresponding image data amount for obtaining also is greatly increased.Due to imaging technique condition limit The difference of system and image-forming principle, for the one side feature that any one single image can only all reflect destination object so that Its range of application is extremely limited.And image fusion technology is exactly effective spy of two or more images to Same Scene Levy the process for blending into new images so that the fusion image of acquisition can more comprehensively reflect clarification of objective, greatly increase data The precision and reliability of analysis.For example for visible light sensor imaging system, in the different image of a width scene depth In, the target focused in image can present clearly image, and with the target before and after other targets of certain distance all will There is different degrees of obscuring.

Used as the Main Branches of Data fusion technique, image co-registration can reduce single image and goal description not known Property, obtain an information more horn of plenty, obscure less, reliability better image in order to people's observation or computer disposal, Its effect includes：Image enhaucament, feature extraction, identification, tracking, classification etc..Image fusion technology is in computer vision, doctor Learn the fields such as image, remote sensing images, military affairs to be widely applied.

Existing image fusion technology will be in order that all targets can present clearly image in scene, first As system is focused in a part of target, a partial target clearly image is obtained, in refocusing another part target, obtained To another partial target clearly image, finally this two width image is merged using blending algorithm, obtained all targets All clearly image (Wang Yajie, Wang Xiaoyan, Liu Xueping. the Overview of multi-focus image fusion [J] based on wavelet transformation. Shenyang navigate Empty engineering institute's journal, 2005,04:65-67).

Existing fusion method has wavelet transform fusion and discrete cosine transform method etc., and both approaches all have fusion Afterwards image border is unintelligible, it may appear that the problem of false contouring.

The content of the invention

It is an object of the invention to provide a kind of based on the two-dimentional multi-focus image fusing method for coupling convolution, the method can be obtained The fusion image of better quality is obtained, the unsharp problem of conventional images integration technology edge details is solved.

The technical solution adopted in the present invention is that a kind of multi-focus image fusing method based on two dimension coupling convolution is wrapped Include following steps：

Step 1, the different image of multiple focus objects is gathered to Same Scene, then carries out image registration；

Step 2, is input into fusion image, I₁,I₂∈R^I×J, and it is divided into the image that L size is M × N with sliding window technology Block,J-th image block of i-th image to be fused is represented, an empty matrix O ∈ R is initialized^I×JAfter storage fusion Image；

Step 3, takes successively j=1,2 ..., L, respectively execution step 3-1 to 3-4；

Step 3-1, by the data modeling of step 2 into single-input multiple output, I^jRepresent input scene,Represent focus function,Represent through different system Output；Build two dimension coupling convolution model：

According to Structural matrix X according to the following formula_j,

Wherein:

Structural matrix Y in the same manner_j；

Step 3-2, calculates according to the following formula R,

R=[X_j-Y_j]^T[X_j-Y_j]

Step 3-3, with the imaging system in Eigenvalues Decomposition computation modelWith Optimal solution it is special for the minimum of R The corresponding characteristic vector of value indicative；Then compareWithVariance, select clearly image block

Step 3-4, pressesOriginally the position in image to be fused, incites somebody to actionIn being stacked to matrix O；

Step 4, for the number of times that each pixel in matrix O is added divided by it, then obtains final output fusion figure Picture.

Of the invention the characteristics of, also resides in：

In step 2P represents sliding window step-length, p<M and p<N.

The invention has the beneficial effects as follows, the method for the present invention compared with the conventional method, can accurately be judged clearly to scheme As block so that fusion image has stronger robustness, can fusion image clearly material particular well, also will not draw Enter artificial vestige.

Description of the drawings

Fig. 1 is imaging system schematic diagram of the present invention；

Fig. 2 is the imaging system schematic diagram of present invention extension；

Fig. 3-1 represents a focusedimage of the first embodiment, and Fig. 3-2 represents another focusedimage, and Fig. 3-f are represented Fusion image；

Fig. 4-1 represents a focusedimage of second embodiment, and Fig. 4-2 represents another focusedimage, and Fig. 4-f are represented Fusion image；

Fig. 5-1 represents a focusedimage of the third embodiment, and Fig. 5-2 represents another focusedimage, and Fig. 5-f are represented Fusion image；

Fig. 6-1 represents a focusedimage of the 4th kind of embodiment, and Fig. 6-2 represents another focusedimage, and Fig. 6-f are represented Fusion image；

Fig. 7 is the inventive method and small wave converting method, discrete cosine transform method fusion Detail contrast figure.

Specific embodiment

With reference to the accompanying drawings and detailed description the present invention is described in further detail, but the present invention is not limited to The embodiment.

The multi-focus image fusing method of the present invention, gathers multiple to Same Scene and focuses on mesh initially with CCD camera The different image of mark, then carries out image registration, and image registration can be carried out using existing method for registering.

Image sliding window technology of the size for I × J is divided into into some image blocks that size is M × N, is usedRepresent J-th image block of i-th image to be fused, sets sliding window step-length p (p<M and p<N).

Although image block is from different images to be fused, they are from the target imaging in same field (only It is that focus level is different), therefore by above-mentioned analysis modeling into single-input multiple output.By taking two output as an example, such as Fig. 1 institutes Show：I^jRepresent input scene,Represent focus function, Represent the output through different system.

The imaging system in model is solved using Eigenvalues Decomposition

According to Fig. 1, we have following expression：

Wherein * represents convolution algorithm, by the commutative law and associative law of two-dimensional convolution, obtains as shown in Fig. 2, formula (3) The imaging system of extension.

Build following two dimension coupling convolution model：

Then, it is based onConstruct following matrix and the convolution form of above-mentioned model is written as into mathematics multiplication form.

Wherein:

In the same manner, willAlso it is written as matrix Y_j, the form that can be multiplied：

Wherein

Abbreviation above formula, and in order to avoidSituation all for 0, increases bound term：

Then have：

Wherein：It is obvious thatOptimal solution be the corresponding spy of minimal eigenvalue of R Levy vector.

Without loss of generality, it is assumed thatIn target be focus on shoot (clear), andIt is to defocus shooting (fuzzy).Cause Solve in this above formulaIt is fuzzy filter to be equivalent to, and is comparedIts variance is smaller.So eventually through calculating Variance can judge Readability.

Based on above-mentioned analysis, the method is performed as steps described below.

The first step：Determine size M of image block, N.Then sliding window step-length p (p is set<M, p<N).

Bis- Walk：Input fusion image, I₁,I₂∈R^I×J, and the image block that L size is M × N is divided into, whereinOne empty matrix O ∈ R of initialization^I×JFor depositing fused data.

3rd step：

Circulation j=1,2 ..., L

①：Pass through Structure is according to (5) (6) formula structural matrix X_j,Y_j。

②：R is calculated (by X_j,Y_j)。

③：Calculated with Eigenvalues Decomposition Then compare Variance, select clearly image block(variance is little Corresponding image block is clearly image block .)

④：WillIt is stacked in O (by position of its original in image to be fused).Loop ends.

4th step：For the number of times that each pixel in O is added divided by it, final output fusion image is then obtained.

Using the method for the present invention multiple focussing image that six width have been aligned is merged respectively.The table in Fig. 3-1 left sides It is to focus on to shoot (imaging clearly), the table on Fig. 3-2 right sides is to focus on to shoot (imaging clearly), and Fig. 3-f are the inventive method Fusion results, it can be seen that the method for the present invention has merged well the focusing photographing section of Fig. 3-1, Fig. 3-2, after fusion The left side of image and all will be apparent that for right side.In the same manner, the table in Fig. 4-1 left sides is to focus on to shoot (imaging clearly), and Fig. 4-2 is right The people of side is to focus on to shoot (imaging clearly), and Fig. 4-f are using the clearly fusion results of the inventive method, the figure after fusion The details such as the table in the left side of picture and the people on right side all will be apparent that.The potted plant of Fig. 5-1 left sides is to focus on to shoot (imaging clearly), figure Clock and watch on the right side of 5-2 are to focus on to shoot (imaging clearly), and Fig. 5-f are, using the clearly fusion results of the inventive method, to melt The details such as potted plant and right side the clock and watch in the left side of the image after conjunction all will be apparent that.Fig. 6-1 flower leopard head be focus on shoot (into As clearly), the foot of Fig. 6-2 flower leopards is to focus on to shoot (imaging clearly), and Fig. 6-f are clearly melting using the inventive method Result is closed, the speckle of the colored leopard body of fused image is integrally all apparent from.The method of the present invention can fusion image well Clearly material particular, will not also introduce artificial vestige.

Fusion method of the present invention is contrasted with traditional Wavelet Transform Fusion method and discrete cosine transform method, such as Fig. 7 Shown, left-side images represent the fusion results of Wavelet Transform Fusion method, and intermediate image represents the fusion knot of discrete cosine transform method Really, the detailed information at the hair edge of both fusions legal person is very unintelligible, and the fusion results of right side the inventive method are carried Gem-pure edge details, effect have been supplied to be substantially better than traditional method.

Claims (2)

1. it is a kind of based on the two-dimentional multi-focus image fusing method for coupling convolution, it is characterised in that to comprise the following steps：

Step 1, the different image of multiple focus objects is gathered to Same Scene, then carries out image registration；

Step 2, is input into fusion image, I₁,I₂∈R^I×J, and the image block that L size is M × N is divided into sliding window technology, J-th image block of i-th image to be fused is represented, an empty matrix O ∈ R is initialized^I×JFor the image after storage fusion；

Step 3, takes successively j=1,2 ..., L, respectively execution step 3-1 to 3-4；

Step 3-1, by the data modeling of step 2 into single-input multiple output, I^jRepresent input scene,Represent focus function,Represent through the defeated of different system Go out；Build two dimension coupling convolution model：

$\underset{F_1^j,F_2^j}{\min }\left|\right|S_1^j*F_1^j-S_2^j*F_1^j|{|}_F^2---\left(4\right)$

According toStructural matrix X according to the following formula_j,

Wherein:

Structural matrix Y in the same manner_j；

Step 3-2, calculates according to the following formula R,

R=[X_j-Y_j]^T[X_j-Y_j]

Step 3-3, with the imaging system in Eigenvalues Decomposition computation modelWithWithOptimal solution it is special for the minimum of R The corresponding characteristic vector of value indicative；Then compareWithVariance, select clearly image block

Step 3-4, pressesOriginally the position in image to be fused, incites somebody to actionIn being stacked to matrix O；

Step 4, for the number of times that each pixel in matrix O is added divided by it, then obtains final output fusion image.

2. it is according to claim 1 based on the two-dimentional multi-focus image fusing method for coupling convolution, it is characterised in that step In 2P represents sliding window step-length, p<M and p<N.