CN108225570A - A kind of adaptive non-uniformity correction algorithm in short-wave infrared focal plane - Google Patents
A kind of adaptive non-uniformity correction algorithm in short-wave infrared focal plane Download PDFInfo
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Abstract
The invention discloses a kind of adaptive non-uniformity correction algorithms in short-wave infrared focal plane, the adaptive non-uniformity correction algorithm in short-wave infrared focal plane carries out regression estimates using the heterogeneity of logistics function combination short-wave infrared focal plane asymmetric model focal planes and Nonuniformity Correction coefficient is obtained, and achievees the purpose that correction.
Description
Technical field
The present invention relates to the technical fields of short-wave infrared focal plane, adaptive non-equal more particularly to short-wave infrared focal plane
Even correcting algorithm.
Background technology
The heterogeneity of short-wave infrared focal plane arrays (FPA) can be with use environment temperature, imageable target temperature, focal plane itself
Temperature, focal plane working time length variation and change, correction coefficient needs real-time update.
It is above-mentioned existing therefore, it is desirable to there is a kind of adaptive non-uniformity correction algorithm in short-wave infrared focal plane that can effectively solve
There is the defects of technology.
Invention content
The purpose of the present invention is to provide a kind of short-wave infrared focal planes based on logistics and multiple-factor calibration model
Adaptive non-uniformity correction algorithm uses logistics function combination short-wave infrared focal plane asymmetric model focal planes
Heterogeneity carry out regression estimates Nonuniformity Correction coefficient is obtained, achieve the purpose that correction.
To achieve the above object, the present invention provides a kind of short-wave infrared based on logistics and multiple-factor calibration model
The adaptive non-uniformity correction algorithm in focal plane includes the following steps:
1. two hypotheses are carried out to linear model;
2. ignoring probe unit, there are under error condition, approx think burnt flat in the smaller saturation with removal of radiation scope
Face response is linear, and under the conditions of uniform radiancy, the heterogeneity linear model of focal plane can be represented by the following formula:
Yk(i, j)=ak(i,j)*Xk(i,j)-bk(i,j)+nk(i,j)
In formula, XkWhen (i, j) represents kth frame, the true infra-red radiation degree that detects member received by of the coordinate for (i, j), ak
(i, j) and bk(i, j) is respectively at this point, the multiplicative noise variable of the probe unit and additive noise variable, nk(i, j) is reads
The electronic noise of circuit, ak(i, j) and bkThe value of (i, j) is also changed over time and is changed simultaneously;
3. the heterogeneity of focal plane 2. can be obtained mainly by the gain of multiplying property and the biasing group of additivity by step
Into influence focal plane asymmetric is mainly to bias, and with environment temperature, detector temperature and the change of working time
Change, be biased in and ceaselessly change, therefore many scene correcting algorithms occur, only to biasing ceaselessly predictive compensation, in scene
Constantly good effect is can be obtained by the case of movement;
4. the combination for the heterogeneity of bias being resolved into a few class impact factors of environment temperature, detector temperature adds one
A fixed mean value biasing forms model:
Yk(i, j)=Ak(i,j)*Xk(i,j)+Bk(i,j)*TFPA+Ck(i,j)*TENV+m
In formula, Ak(i, j) and Bk(i,j)、Ck(i, j) is respectively that focal plane asymmetric response coefficient, detector temperature are non-
Uniformity coefficient, working time heterogeneity coefficient, m are fixed mean value biasings, can be ignored in correction;
5. gray scale is continuous between assuming the pixel of infrared focal plane imaging, then in infrared image between adjacent picture elements
Difference is very little in the statistical significance of certain frame number, it means that two adjacent picture elements are almost on the histogram of time
Equal;
6. the true response approximation of single probe unit is equal to according to the hypothesis of step 5. by neighborhood detection member response
Mean value Y, so as to the estimated value returned as logistics:
Then the logistics function models of nonuniformity correction estimated value are
7. according to above-mentioned nonuniformity correction model, the logistics function models of nonuniformity correction are:
8. using maximal possibility estimation, the parameter of Nonuniformity Correction, such as following formula is obtained:
Solve Ak(i, j) and Bk(i,j)、Ck(i, j) focal plane asymmetric response coefficient, detector temperature heterogeneity
Coefficient, working time heterogeneity coefficient, specific solve can use newton-La Feisen alternative manners to solve.
Preferably, two hypotheses of the linear model include:(1) response of each probe unit exists in focal plane
It is stable on time, will not changes because of working time length;(2) working region of each probe unit is linear.
For the deficiency that this non-homogeneous feature of short-wave infrared focal plane and shutter correct, the present invention provides one kind to be based on
The adaptive non-uniformity correction algorithm in short-wave infrared focal plane of logistics and multiple-factor calibration model, the algorithm Comprehensive
The considerations of arrived each heteropical impact factor of environment temperature, explorer response, detector temperature, so as to solving well
The uncertainty of shortwave focal plane asymmetric correction, quantitative test the result shows that, this method can reach 0.001% it is non-
Even property correction is remaining, significantly improves correction accuracy, improves the picture quality of infrared imaging, expands being applicable in for alignment technique
Range.
Specific embodiment
The adaptive non-uniformity correction algorithm in short-wave infrared focal plane based on logistics and multiple-factor calibration model includes
Following steps:
1. two hypotheses of traditional linear model:First, the response of each probe unit is in time in focal plane
It is stable, will not changes because of working time length;Second is that the working region of each probe unit is linear;
2. ignoring probe unit, there are under error condition, approx think burnt flat in the smaller saturation with removal of radiation scope
Face response is linear, and under the conditions of uniform radiancy, the heterogeneity linear model of focal plane can be represented by the following formula:
Yk(i, j)=ak(i,j)*Xk(i,j)-bk(i,j)+nk(i,j)
In formula, XkWhen (i, j) represents kth frame, the true infra-red radiation degree that detects member received by of the coordinate for (i, j), ak
(i, j) and bk(i, j) is respectively at this point, the multiplicative noise variable of the probe unit and additive noise variable, nk(i, j) is reads
The electronic noise of circuit, ak(i, j) and bkThe value of (i, j) is also changed over time and is changed simultaneously;
3. the heterogeneity of focal plane 2. can be obtained mainly by the gain of multiplying property and the biasing group of additivity by step
Into influence focal plane asymmetric is mainly to bias, and with environment temperature, detector temperature and the change of working time
Change, be biased in and ceaselessly change, therefore many scene correcting algorithms occur, only to biasing ceaselessly predictive compensation, in scene
Constantly good effect is can be obtained by the case of movement;
4. the combination for the heterogeneity of bias being resolved into a few class impact factors of environment temperature, detector temperature adds one
A fixed mean value biasing forms model:
Yk(i, j)=Ak(i,j)*Xk(i,j)+Bk(i,j)*TFPA+Ck(i,j)*TENV+m
In formula, Ak(i, j) and Bk(i,j)、Ck(i, j) is respectively that focal plane asymmetric response coefficient, detector temperature are non-
Uniformity coefficient, working time heterogeneity coefficient, m are fixed mean value biasings, can be ignored in correction;
5. gray scale is continuous between assuming the pixel of infrared focal plane imaging, then in infrared image between adjacent picture elements
Difference is very little in the statistical significance of certain frame number, it means that two adjacent picture elements are almost on the histogram of time
Equal;
6. the true response approximation of single probe unit is equal to according to the hypothesis of step 5. by neighborhood detection member response
Mean value Y, so as to the estimated value returned as logistics:
Then the logistics function models of nonuniformity correction estimated value are
7. according to above-mentioned nonuniformity correction model, the logistics function models of nonuniformity correction are:
8. using maximal possibility estimation, the parameter of Nonuniformity Correction, such as following formula is obtained:
Solve Ak(i, j) and Bk(i,j)、Ck(i, j) focal plane asymmetric response coefficient, detector temperature heterogeneity
Coefficient, working time heterogeneity coefficient, specific solve can use newton-La Feisen alternative manners to solve.
In practical application, with gradient ascent algorithm, iteration continues always.Gradient ascent algorithm is compared with Newton iteration,
Convergence rate is slow, because gradient ascent algorithm is single order convergence, and Newton iteration belongs to second order convergence.
Above-mentioned algorithm practical application, the logistics estimation windows of correction are 3 × 3 statistical window, are risen by gradient
Method, generally converges to optimal in 100 frame image post-equalization coefficients, and image is more uniform after correction, and calibration result is more apparent, and should
Algorithm is not in exaggerated correction when scene stillness or slow movement, leads to " ghost due to using multivariate calibration model
Shadow " without scene motion, calculates simply convenient for real-time parallel processing, breaches the practicability limit of adaptive nonuniformity correction
System
It is last it is to be noted that:The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations.To the greatest extent
Pipe is with reference to the foregoing embodiments described in detail the present invention, it will be understood by those of ordinary skill in the art that:It is still
It can modify to the technical solution recorded in foregoing embodiments or which part technical characteristic is equally replaced
It changes;And these modifications or replacement, the essence for various embodiments of the present invention technical solution that it does not separate the essence of the corresponding technical solution
God and range.
Claims (2)
1. a kind of adaptive non-uniformity correction algorithm in short-wave infrared focal plane, which is characterized in that include the following steps:
1. two hypotheses are carried out to linear model;
2. ignoring probe unit, there are under error condition, approx think focal plane sound in the smaller saturation with removal of radiation scope
Should be linear, under the conditions of uniform radiancy, the heterogeneity linear model of focal plane can be represented by the following formula:
Yk(i, j)=ak(i,j)*Xk(i,j)-bk(i,j)+nk(i,j)
In formula, XkWhen (i, j) represents kth frame, the true infra-red radiation degree that detects member received by of the coordinate for (i, j), ak(i,
And b j)k(i, j) is respectively at this point, the multiplicative noise variable of the probe unit and additive noise variable, nk(i, j) is reading circuit
Electronic noise, ak(i, j) and bkThe value of (i, j) is also changed over time and is changed simultaneously;
3. it 2. can show that the heterogeneity of focal plane is mainly made of the gain of multiplying property and the biasing of additivity by step, shadow
Mainly biasing for focal plane asymmetric is rung, and with environment temperature, detector temperature and the variation of working time, biasing
Ceaselessly changing, therefore many scene correcting algorithms occurring, only to biasing ceaselessly predictive compensation, constantly moved in scene
In the case of can be obtained by good effect;
4. the combination for the heterogeneity of bias being resolved into a few class impact factors of environment temperature, detector temperature is solid plus one
Fixed mean value biasing forms model:
Yk(i, j)=Ak(i,j)*Xk(i,j)+Bk(i,j)*TFPA+Ck(i,j)*TENV+m
In formula, Ak(i, j) and Bk(i,j)、Ck(i, j) is respectively that focal plane asymmetric response coefficient, detector temperature are non-homogeneous
Property coefficient, working time heterogeneity coefficient, m are fixed mean value biasings, can be ignored in correction;
5. gray scale is continuous between assuming the pixel of infrared focal plane imaging, then the difference in infrared image between adjacent picture elements
It is very little in the statistical significance of certain frame number, it means that two adjacent picture elements are almost equal on the histogram of time
's;
6. the true response approximation of single probe unit is equal to according to the hypothesis of step 5. by neighborhood detection member response mean value
Y, so as to the estimated value returned as logistics:
Then the logistics function models of nonuniformity correction estimated value are
7. according to above-mentioned nonuniformity correction model, the logistics function models of nonuniformity correction are:
8. using maximal possibility estimation, the parameter of Nonuniformity Correction, such as following formula is obtained:
Solve Ak(i, j) and Bk(i,j)、Ck(i, j) focal plane asymmetric response coefficient, detector temperature heterogeneity coefficient,
Working time heterogeneity coefficient, specific solve can use newton-La Feisen alternative manners to solve.
2. the adaptive non-uniformity correction algorithm in short-wave infrared focal plane as described in claim 1, it is characterised in that:It is described linear
Two hypotheses of model include:(1) in focal plane the response of each probe unit be in time it is stable, will not be because of
Working time length and change;(2) working region of each probe unit is linear.
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CN111678605A (en) * | 2020-06-17 | 2020-09-18 | 北京中云微迅信息技术有限公司 | Infrared temperature measurement compensation method based on thermopile electricity |
CN111998961A (en) * | 2020-09-23 | 2020-11-27 | 国科天成(北京)科技有限公司 | Infrared focal plane non-uniformity correction method based on pixel point temperature drift estimation |
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