CN107967449A - A kind of multispectral image unknown object recognition methods based on broad sense evidence theory - Google Patents

A kind of multispectral image unknown object recognition methods based on broad sense evidence theory Download PDF

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CN107967449A
CN107967449A CN201711135254.4A CN201711135254A CN107967449A CN 107967449 A CN107967449 A CN 107967449A CN 201711135254 A CN201711135254 A CN 201711135254A CN 107967449 A CN107967449 A CN 107967449A
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蒋雯
胡伟伟
邓鑫洋
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Northwestern Polytechnical University
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Abstract

The present invention is based on multispectral image, there is provided a kind of to realize that unknown object knows method for distinguishing under the sky background of face, is related to target identification, image processing field with broad sense evidence theory.The present invention establishes triangle fuzzy model to target, cloud, sky, will classify after model broadening to pixel, determines whether unknown object according to pixel classification results, and update current Triangular Fuzzy Number model with pixel classification results.The present invention classifies pixel using broad sense evidence theory, this sorting technique has preferably merged the image information of different-waveband, can realize the differentiation of unknown object, has the advantages that calculating is simple, real-time is good；Random disturbances method for removing proposed by the present invention, eliminates erroneous judgement caused by random disturbances well.

Description

A kind of multispectral image unknown object recognition methods based on broad sense evidence theory
Technical field
The present invention relates to target identification, image processing field, is that one kind is realized under the sky background of face based on broad sense evidence theory Multispectral image unknown object knows method for distinguishing.
Background technology
Under battlefield surroundings, the main object of target identification is the Aircraft Targets for rushing and invading by mistake China territorial sky, comprising non- Cooperative target and hostile target.From the point of view of machine learning, when tupe identifies problem, researcher is needed to being possible to The target classification of appearance establishes masterplate database, and chooses wherein all target class and be very originally trained.However, non-cooperative target Mark and hostile target can not establish its full database.When Aircraft Targets are the unknown objects outside database, that is, it is non- It is imperfect due to its database when cooperative target or hostile target, easily by the target be mistaken for database other known to Target.By mistake by enemy's aircraft be determined as our aircraft or our aircraft is mistaken for enemy's aircraft all can be after bringing on a disaster property Fruit, therefore studying unknown object recognition methods has important military value.
Information fusion technology is that collaboration utilizes multi-source information, to obtain more objective to things or target, more essential understanding Informix treatment technology, is one of key technology of intelligence science research.In many information fusion models and method, extensively Adopted evidence theory (Generalized Evidence Theory, GET) algorithm is one of maximally efficient algorithm.Broad sense evidence Theoretical starting point is an open world based on the environment residing for emerging system, uses empty setTo model open world, give upLimitation.In broad sense evidence theoryIt is not traditional empty set, it is outside framework of identification that it is corresponding Proposition.Broad sense evidence theory proposes broad sense Basic probability assignment function (Generalized Basic Probability Assignment, GBPA), and propose the fusion that broad sense composite formula realizes two GBPA.When system is in closed world, Exactly meetWhen, broad sense evidence theory just deteriorates to the evidence theory of classics, from this view point, broad sense evidence reason By being that classical evidence theory is simple and intuitively promote.
There has been no the research that unknown object identification is realized based on multispectral image at present.Broad sense evidence theory has many excellent Point, applied has important military value in the identification of multispectral image unknown object.
The content of the invention
In order to realize that unknown object identifies, the present invention is based on multispectral image, there is provided one kind is realized with broad sense evidence theory Unknown object knows method for distinguishing under the sky background of face, and the identification of hostile unknown object is realized while current goal is tracked.Use The unknown object identification that this method is realized has important military value.
The technical solution adopted by the present invention to solve the technical problems includes the following steps：
Step 1：Input each wave band cloud (C) under a pattern sky multispectral image and current environment, sky (S) and current Minimum gray value, intermediate value and the maximum of target (T) imaging, according to the gray scale of the cloud, sky and current goal of input imaging most Small value, intermediate value, maximum, establish corresponding Triangular Fuzzy Number model, and the current goal is the tracking target of current interest (such as Defensive Target), framework of identification areC represents cloud in framework of identification, and S represents sky, and T represents current mesh Mark,Represent unknown object, C, S, the method for T Triangular Fuzzy Number model foundations is：
The minimum gray value Cmin that wave band i clouds are imagedi, intermediate value CaveiAnd maximum CmaxiRespectively as wave band i clouds three The minimum value of angle Fuzzy Math Model, intermediate value, maximum, then the Triangular Fuzzy Number of wave band i clouds be The minimum gray value Smin that wave band i skies are imagedi, intermediate value SaveiAnd maximum SmaxiRespectively as wave band i sky Triangle Modules The minimum value of paste exponential model, intermediate value, maximum, the then Triangular Fuzzy Number that wave band i skies are established are The minimum gray value Tmin that wave band i current goals are imagedi, intermediate value TaveiAnd maximum of T maxiRespectively as the current mesh of wave band i The minimum value of mark Triangular Fuzzy Number model, intermediate value, maximum, the then Triangular Fuzzy Number that wave band i current goals are established are
Step 2：The fuzzy number broadening that step 1 is obtained, i.e., reduce the upper bound increase of fuzzy number, lower bound, remember respectively Fuzzy number after cloud, sky, current goal broadening isThe method for widening is：
Step 3：Classify to any pixel point p in input picture, classification results may be cloud, sky, current mesh Mark, unknown object：
1) to any classified pixels point p, its wave band i gray values G is takeni, use GiWithIt is basic to generate broad sense Probability distribution function mi, it is describedRespectively foregoing wave band i clouds, sky, the Triangular Fuzzy Number of current goal, The broad sense Basic probability assignment function is defined as the subset A, m (A) for belonging to Θ to any one in broad sense evidence theory ∈ [0,1], and meetThen m is 2ΘOn broad sense Basic probability assignment function, wherein 2ΘFor the power of framework of identification Collection,The broad sense Basic probability assignment function mi Generation method is：By GiWith fuzzy numberThe high point of intersection point is assigned to the reliability of corresponding single subset elements, by GiWith Fuzzy numberThe secondary high point of intersection point is assigned to the reliability of corresponding double subset elements, by GiWith fuzzy numberThe low spot of intersection point is assigned to the reliability of corresponding more subset elements, wherein single subset elements refer to walking The subset { C } of framework of identification Θ, { S } or { T }, double subset elements refer to framework of identification Θ in step 1 in rapid one Subset { C, S }, { C, T } or { S, T }, more subset elements refer to the subset { C, S, T } of framework of identification Θ in step 1；Note The sum of reliability of generation is Sum, if Sum is not less than 1, the reliability of generation is normalized to obtain mi；If Sum is less than 1, by 1- Sum is assigned to empty setReliability；
2) by the broad sense Basic probability assignment function m of 25 wave band generationsiMerge to obtain m using average fusion method, institute Stating average fusion method is：Whereinmi(i=1,2 ..., 25) it is to be generated in step 2 Broad sense Basic probability assignment function；
3) m after fusion is converted into probability point using Pignistic probability transformation methods Cloth P, the conversion method are： Wherein
4) classify according to obtained probability distribution P to pixel p, take P ({ C }), P ({ S }), P ({ T }),In most The corresponding classification of big probability as pixel p classify as a result, C represents cloud in classification results, S represents sky, and T represents current Target,Represent unknown object；
Step 4：ELIMINATION OF ITS INTERFERENCE is carried out to the region for being categorized as unknown object, to choose real movement unknown object, is done The principle for disturbing exclusion is realized using the position correlation of consecutive frame zone of ignorance：
If knowing caused by random disturbances by mistake, then the change in location of consecutive frame zone of ignorance is larger, sets rational threshold value Random disturbances can be excluded, threshold value can be chosen according to target speed and (such as elect 1.5 times of target single frames displacements as)；If static Target, after 5-10 frames its total displacement be able to can equally be excluded close to 0；
Step 5：Obscured according to the triangle of the pixel classification results of present frame renewal previous frame current goal, cloud, sky Exponential model, it is described using the model after renewal as next two field picture cloud, sky, the other Fuzzy Math Model of three species of current goal Model update method is：
For all pixels for being identified as cloud, the maximum max and minimum value min of these pixel wave bands i are obtained, If max>Cmaxi, willThe upper bound is updated to max, if min<Cmini, willLower bound is updated to min；It is identified as day for all Empty pixel, obtains the maximum max and minimum value min of these pixel wave bands i, if max>Smaxi, willThe upper bound updates For max, if min<Smini, willLower bound is updated to min；For all pixels for being identified as current goal, these are obtained The maximum max and minimum value min of pixel wave band i, if max>Tmaxi, willThe upper bound is updated to max, if min<Tmini, willLower bound is updated to min.
Classified the beneficial effects of the present invention are the present invention using broad sense evidence theory to pixel, can be according to pixel Classification results select current goal and it are tracked, and realize the differentiation of unknown object, therefore sorting technique proposed by the present invention The preferable image information for having merged different-waveband, has the advantages that calculating is simple, real-time is good；Triangle Module proposed by the present invention Number modeling method is pasted, the problem of representation for solving fuzzy message well；Broad sense Basic probability assignment function proposed by the present invention Generation method, realizes the processing to fuzzy message well；Random disturbances method for removing proposed by the present invention, excludes well Erroneous judgement caused by random disturbances.
Brief description of the drawings
The general flow chart that Fig. 1 present invention realizes.
Fig. 2 is the other fuzzy number of 1 three species of wave band.
Fig. 3 is the fuzzy number after 1 three kinds of classification broadenings of wave band.
Embodiment
The present invention is further described with example below in conjunction with the accompanying drawings.
Step 1：Input each wave band cloud (C), sky under the face sky multispectral image and current environment of 25 wave band of a frame (S) and current goal (T) imaging minimum gray value, intermediate value and maximum, according to the cloud, sky and current goal of input be imaged Minimum gray value, intermediate value, maximum, establish corresponding Triangular Fuzzy Number model, the current goal is current interest Target (such as Defensive Target) is tracked, framework of identification isC represents cloud in framework of identification, and S represents sky, T tables Show current goal,Represent unknown object, C, S, the method for T Triangular Fuzzy Number model foundations is：
Minimum gray value 131, intermediate value 172.5 and the maximum 214 of 1 cloud of wave band imaging are inputted, respectively as 1 cloud three of wave band The minimum value of angle Fuzzy Math Model, intermediate value, maximum, then the Triangular Fuzzy Number of 1 cloud of wave band beWill Minimum gray value 91, intermediate value 140 and the maximum 189 of 1 sky of wave band imaging are respectively as 1 sky Triangular Fuzzy Number model of wave band Minimum value, intermediate value, maximum, then 1 sky of wave band establish Triangular Fuzzy Number beWave band 1 is current The minimum gray value 69 of target imaging, 109.5 maximum 150 of intermediate value are respectively as 1 current goal Triangular Fuzzy Number model of wave band Minimum value, intermediate value, maximum, then 1 current goal of wave band establish Triangular Fuzzy Number be
Step 2：The fuzzy number broadening that step 1 is obtained, the fuzzy number after cloud, sky, current goal broadening are remembered respectively ForThe method for widening is：
WithBroadening exemplified by, the result after broadening is：
Step 3：Classify to any pixel point p in input picture, classification results may be cloud, sky, current mesh Mark, unknown object：
1) to any classified pixels point p, its wave band i gray values G is takeni, use GiWithIt is basic to generate broad sense Probability distribution function mi, it is describedRespectively foregoing wave band i clouds, sky, the Triangular Fuzzy Number of current goal, The broad sense Basic probability assignment function is defined as the subset A, m (A) for belonging to Θ to any one in broad sense evidence theory ∈ [0,1], and meetThen m is 2ΘOn broad sense Basic probability assignment function, wherein 2ΘFor the power of framework of identification Collection,The broad sense Basic probability assignment function mi Generation method is：By GiWith fuzzy numberThe high point of intersection point is assigned to the reliability of corresponding single subset elements, by GiWith Fuzzy numberThe secondary high point of intersection point is assigned to the reliability of corresponding double subset elements, by GiWith fuzzy numberThe low spot of intersection point is assigned to the reliability of corresponding more subset elements, wherein single subset elements refer to walking The subset { C } of framework of identification Θ, { S } or { T }, double subset elements refer to framework of identification Θ in step 1 in rapid one Subset { C, S }, { C, T } or { S, T }, more subset elements refer to the subset { C, S, T } of framework of identification Θ in step 1；Note The sum of reliability of generation is Sum, if Sum is not less than 1, the reliability of generation is normalized to obtain mi；If Sum is less than 1, by 1- Sum is assigned to empty setReliability；
The pixel p of input is 71 in the gray value of wave band 1, then m1Generation method is as follows：
Such as Fig. 3, gray value 71 withThere is an intersection point 0.3636, as the reliability of current goal (T).Sum at this time =T=0.3636, unknown object is distributed to by 1-Sum i.e. 0.6364Reliability.Obtain m1：
m1{ T }=0.3636,
With same method, m is obtained2~m25It is as follows：
m2{ T }=0.5417, m2{ S, T }=0.0471,
m3{ T }=0.3925,
m4{ T }=0.4,
m5{ T }=0.5495, m5{ S, T }=0.1059,
m6{ T }=0.3667,
m7{ T }=0.3524,
m8{ T }=0.3420,
m9{ T }=0.4609, m9{ S, T }=0.3833,
m10{ T }=0.3939, m10{ S, T }=0.0175,
m11{ T }=0.1739,
m12{ T }=0.4608, m12{ S, T }=0.0833,
m13{ T }=0.3770, m13{ S, T }=0.0804,
m14{ T }=0.3489, m14{ S, T }=0.1429,
m15{ T }=0.4186, m15{ S, T }=0.0545,
m16{ T }=0.3904, m16{ S, T }=0.0294,
m17{ T }=0.5552, m17{ C, T }=0.4448
m18{ T }=0.4775, m18{ S, T }=0.0706,
m19{ T }=0.3738,
m20{ T }=0.4587,
m21{ T }=0.5794,
m22{ T }=0.5536,
m23{ T }=0.4587,
m24{ T }=0.5287,
m25{ T }=0.4800,
2) by the broad sense Basic probability assignment function m of 25 wave band generationsiMerge to obtain m using average fusion method, institute Stating average fusion method is：Whereinmi(i=1,2 ..., 25) it is what is generated in step 2 Broad sense Basic probability assignment function；
Fusion results are：M { T }=0.4319, m { S, T }=0.0584,
3) m after fusion is converted into probability point using Pignistic probability transformation methods Cloth P, the conversion method are： Wherein
The result that m is converted to probability distribution P is
P { T }=0.4611, P { S }=0.0292,
4) classify according to obtained probability distribution P to pixel p, take P ({ C }), P ({ S }), P ({ T }),In most The corresponding classification of big probability as pixel p classify as a result, C represents cloud in classification results, S represents sky, and T represents current Target,Represent unknown object；
According to probability distribution P, maximum probability classification isTherefore pixel p is classified as unknown object.
Step 4：ELIMINATION OF ITS INTERFERENCE is carried out to the region for being categorized as unknown object, to choose real movement unknown object, is done The principle for disturbing exclusion is realized using the position correlation of consecutive frame zone of ignorance：
If knowing caused by random disturbances by mistake, then the change in location of consecutive frame zone of ignorance is larger, sets rational threshold value Random disturbances can be excluded, threshold value can be chosen according to target speed and (such as elect 1.5 times of target single frames displacements as)；If static Target, after 5-10 frames its total displacement be able to can equally be excluded close to 0；
Step 5：Obscured according to the triangle of the pixel classification results of present frame renewal previous frame current goal, cloud, sky Exponential model, it is described using the model after renewal as next two field picture cloud, sky, the other Fuzzy Math Model of three species of current goal Model update method is：
For all pixels for being identified as cloud, the maximum max and minimum value min of these pixel wave bands i are obtained, If max>Cmaxi, willThe upper bound is updated to max, if min<Cmini, willLower bound is updated to min；It is identified as day for all Empty pixel, obtains the maximum max and minimum value min of these pixel wave bands i, if max>Smaxi, willThe upper bound updates For max, if min<Smini, willLower bound is updated to min；For all pixels for being identified as current goal, these are obtained The maximum max and minimum value min of pixel wave band i, if max>Tmaxi, willThe upper bound is updated to max, if min<Tmini, willLower bound is updated to min.
By taking 1 model modification of wave band as an example：For all pixels for being identified as cloud, these pixel wave bands 1 are obtained Maximum is 214, minimum value 131,Upper bound lower bound does not update；For all pixels for being identified as sky, obtain The maximum of these pixel wave bands 1 is 189, minimum value 87, therefore willLower bound is updated to 87,The upper bound does not update；For All pixels for being identified as current goal, the maximum for obtaining these pixel wave bands 1 are 150, minimum value 65,65< 69, therefore willLower bound is updated to 69,The upper bound does not update.

Claims (1)

1. a kind of multispectral image unknown object method of discrimination based on broad sense evidence theory, it is characterised in that including following steps Suddenly：
Step 1：Input each wave band cloud (C), sky (S) and current goal under a pattern sky multispectral image and current environment (T) minimum gray value, intermediate value and the maximum of imaging, the minimum gray value being imaged according to the cloud, sky and current goal of input, Intermediate value, maximum, establish corresponding Triangular Fuzzy Number model, and the current goal is (such as anti-for the tracking target of current interest Imperial target), framework of identification isC represents cloud in framework of identification, and S represents sky, and T represents current goal,Table Show unknown object, C, S, the method for T Triangular Fuzzy Number model foundations is：
The minimum gray value Cmin that wave band i clouds are imagedi, intermediate value CaveiAnd maximum CmaxiRespectively as wave band i cloud Triangle Modules Paste exponential model minimum value, intermediate value, maximum, then the Triangular Fuzzy Number of wave band i clouds beWill The minimum gray value Smin of wave band i skies imagingi, intermediate value SaveiAnd maximum SmaxiObscured respectively as wave band i sky triangles The minimum value of exponential model, intermediate value, maximum, the then Triangular Fuzzy Number that wave band i skies are established are The minimum gray value Tmin that wave band i current goals are imagedi, intermediate value TaveiAnd maximum of T maxiRespectively as the current mesh of wave band i The minimum value of mark Triangular Fuzzy Number model, intermediate value, maximum, the then Triangular Fuzzy Number that wave band i current goals are established are
Step 2：The fuzzy number broadening that step 1 is obtained, i.e., reduce the upper bound increase of fuzzy number, lower bound, remember cloud, day respectively Fuzzy number after empty, current goal broadening isThe method for widening is：
<mrow> <mi>E</mi> <msub> <mover> <mi>C</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>Cmin</mi> <mi>i</mi> </msub> <mo>-</mo> <mn>10</mn> <mo>,</mo> <msub> <mi>Cave</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>Cmax</mi> <mi>i</mi> </msub> <mo>+</mo> <mn>10</mn> <mo>)</mo> </mrow> <mo>,</mo> <mi>E</mi> <msub> <mover> <mi>S</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>Smin</mi> <mi>i</mi> </msub> <mo>-</mo> <mn>10</mn> <mo>,</mo> <msub> <mi>Save</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>Smax</mi> <mi>i</mi> </msub> <mo>+</mo> <mn>10</mn> <mo>)</mo> </mrow> <mo>,</mo> </mrow>
<mrow> <mi>E</mi> <msub> <mover> <mi>T</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>Tmin</mi> <mi>i</mi> </msub> <mo>-</mo> <mn>20</mn> <mo>,</mo> <msub> <mi>Tave</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>Tmax</mi> <mi>i</mi> </msub> <mo>+</mo> <mn>20</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
Step 3：Classify to any pixel point p in input picture, classification results may be cloud, sky, current goal, not Know target：
1) to any classified pixels point p, its wave band i gray values G is takeni, use GiWithGenerate broad sense elementary probability Partition function mi, it is describedRespectively foregoing wave band i clouds, sky, the Triangular Fuzzy Number of current goal, it is described Broad sense Basic probability assignment function be defined as in broad sense evidence theory to any one belong to Θ subset A, m (A) ∈ [0, 1], and meetThen m is 2ΘOn broad sense Basic probability assignment function, wherein 2ΘFor the power set of framework of identification,The broad sense Basic probability assignment function miGeneration Method is：By GiWith fuzzy numberThe high point of intersection point is assigned to the reliability of corresponding single subset elements, by GiWith obscuring NumberThe secondary high point of intersection point is assigned to the reliability of corresponding double subset elements, by GiWith fuzzy number The low spot of intersection point is assigned to the reliability of corresponding more subset elements, wherein single subset elements refer to framework of identification in step 1 The subset { C } of Θ, { S } or { T }, double subset elements refer to the subset { C, S } of framework of identification Θ in step 1, C, T } or { S, T }, more subset elements refer to the subset { C, S, T } of framework of identification Θ in step 1；Remember generation reliability it With for Sum, if Sum is not less than 1, the reliability of generation is normalized to obtain mi；If Sum is less than 1,1-Sum is assigned to empty setReliability；
2) by the broad sense Basic probability assignment function m of 25 wave band generationsiMerge to obtain m using average fusion method, it is described average Fusion method is：Whereinmi(i=1,2 ..., 25) it is the generalized base generated in step 2 This probability distribution function；
3) m after fusion is converted into probability distribution P using Pignistic probability transformation methods, The conversion method is： Wherein
4) classify according to obtained probability distribution P to pixel p, take P ({ C }), P ({ S }), P ({ T }),It is middle maximum The corresponding classification of probability as pixel p classify as a result, C represents cloud in classification results, S represents sky, and T represents current mesh Mark,Represent unknown object；
Step 4：ELIMINATION OF ITS INTERFERENCE is carried out to the region for being categorized as unknown object, to choose real movement unknown object, interference row The principle removed is realized using the position correlation of consecutive frame zone of ignorance：
If knowing caused by random disturbances by mistake, then the change in location of consecutive frame zone of ignorance is larger, sets rational threshold value Random disturbances are excluded, threshold value can be chosen according to target speed and (such as elect 1.5 times of target single frames displacements as)；If static mesh Mark, after 5-10 frames its total displacement be able to can equally be excluded close to 0；
Step 5：The Triangular Fuzzy Number mould of previous frame current goal, cloud, sky is updated according to the pixel classification results of present frame Type, using the model after renewal as next two field picture cloud, sky, the other Fuzzy Math Model of three species of current goal, the model Update method is：
For all pixels for being identified as cloud, the maximum max and minimum value min of these pixel wave bands i are obtained, if max>Cmaxi, willThe upper bound is updated to max, if min<Cmini, willLower bound is updated to min；It is identified as sky for all Pixel, the maximum max and minimum value min of these pixel wave bands i are obtained, if max>Smaxi, willThe upper bound is updated to Max, if min<Smini, willLower bound is updated to min；For all pixels for being identified as current goal, these pictures are obtained The maximum max and minimum value min of vegetarian refreshments wave band i, if max>Tmaxi, willThe upper bound is updated to max, if min<Tmini, will Lower bound is updated to min.
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