CN105865748B - A kind of test method of the imaging sensor critical performance parameters based on particle cluster algorithm - Google Patents
A kind of test method of the imaging sensor critical performance parameters based on particle cluster algorithm Download PDFInfo
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- CN105865748B CN105865748B CN201610297894.4A CN201610297894A CN105865748B CN 105865748 B CN105865748 B CN 105865748B CN 201610297894 A CN201610297894 A CN 201610297894A CN 105865748 B CN105865748 B CN 105865748B
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Abstract
The invention belongs to field of photoelectric technology, are specially related to a kind of test method of the imaging sensor critical performance parameters based on particle cluster algorithm.It specifically includes：Operation is exposed to imaging sensor, n different time for exposure is taken, then acquire n frame light field data and n frame details in a play not acted out on stage, but told through dialogues data respectively, is required according to EMVAStandard1288, calculate light field value varianceLight field gray value mean μy, details in a play not acted out on stage, but told through dialogues gray value μydark；Carry out the specific steps of particle cluster algorithm inverting.The present invention can quickly and conveniently obtain system gain and dark noise parameter.
Description
Technical field
The invention belongs to field of photoelectric technology, and it is key to be specially related to a kind of imaging sensor based on particle cluster algorithm
The test method of energy parameter.
Background technology
Imaging sensor development speed is fast, it is made to be applied to the various aspects of people's social life.From most close to
The application of life such as digital camera, smart mobile phone, security monitoring camera, to the closely bound up novel force of national defense safety
Device or even the highest of mankind's development in science and technology embody --- and space science has the figure of imaging sensor.It is answered with important in production
With field, it is desirable that sensor core piece performance is tested, evaluated and screened, to monitor product quality or ensure the reliable of application
Property.In the measured parameter of imaging sensor, basis and important parameter are the system gain and details in a play not acted out on stage, but told through dialogues noise of sensor the most.
Particle cluster algorithm is also referred to as particle swarm optimization algorithm, is a kind of new evolution algorithm developed in recent years, it
Be from RANDOM SOLUTION, by iteration find optimal solution, solve quality using fitness evaluation, follow current search arrive it is optimal
Value finds global optimum.The advantages that this algorithm is easy to implement with its, precision is high, convergence is fast has obtained the attention of academia,
And its superiority is illustrated in solving practical problems.
Invention content
It is an object of the invention to provide a kind of test of the imaging sensor critical performance parameters based on particle cluster algorithm
Method.
The object of the present invention is achieved like this：
The test method of imaging sensor critical performance parameters based on particle cluster algorithm, includes following steps：
(1) operation is exposed to imaging sensor, takes n different time for exposure, then acquire n frame light field data respectively
It with n frame details in a play not acted out on stage, but told through dialogues data, is required according to EMVAStandard1288, calculates light field value varianceLight field gray value mean μy, it is dark
Field gray value μydark；
(2) particle cluster algorithm inverting is carried out to be as follows：
(2.1) by the system gain K of imaging sensor, dark current μI, initial dark signal varianceForm three dimensional particles；
(2.2) set particle individual adaptation degree function as：
Wherein,It is light field gray value variance, K is system gain, μd.0For dark signal initial value, μIFor dark current, texpFor
Time for exposure, σqFor quantizing noise；
(2.3) according to the optimizing flow of particle cluster algorithm obtain system gain, dark current, initial dark signal variance it is optimal
Estimated value.
The beneficial effects of the present invention are：
The present invention can quickly and conveniently obtain system gain and dark noise parameter.
Description of the drawings
Fig. 1 is step schematic diagram of the present invention.
Specific implementation mode
The present invention is described further below in conjunction with the accompanying drawings.
The invention discloses a kind of based on particle cluster algorithm to the optimization method of imaging sensor parameter, in light field and details in a play not acted out on stage, but told through dialogues
Under the conditions of to imaging sensor multiple exposure, and according to " EMVAStandard1288 " (European Machine Vision Association formulate figure
As sensor and camera testing standard) light field variance, light field mean value, details in a play not acted out on stage, but told through dialogues mean value are calculated separately, and these data and institute are right
The time for exposure data answered are applied to particle cluster algorithm.According to photon replacement theory, fitness function is designed, and by image sensing
System gain K, the dark current μ of deviceI, initial dark signal varianceThree dimensional particles are formed, can be obtained after particle cluster algorithm optimizing
The inversion result of system gain, dark current and initial dark signal variance.This method is insensitive to details in a play not acted out on stage, but told through dialogues variance
The present invention is based on population optimizing algorithms, carry out inverting to imaging sensor key parameter, include the following steps：
S1：Operation is exposed to imaging sensor, takes n different time for exposure, then acquire n frame light field data respectively
With n frame details in a play not acted out on stage, but told through dialogues data.According to the requirement of EMVAStandard1288 standards, light field value variance is calculatedLight field gray value mean value
μy, details in a play not acted out on stage, but told through dialogues gray value μydark；
S2：Particle cluster algorithm inverting is carried out to be as follows：
S2.1：By the system gain K of imaging sensor, dark current μI, initial dark signal varianceForm three dimensional particles；
S2.2：Set particle individual adaptation degree function as：
Wherein,It is light field gray value variance, K is system gain, μd.0For dark signal initial value, μIFor dark current, texpFor
Time for exposure, σqFor quantizing noise；
S2.3：According to the optimizing flow of particle cluster algorithm obtain system gain, dark current, initial dark signal variance it is optimal
Estimated value.
The present invention is in the imaging sensor testing standard EMVAStandard1288 (images that European Machine Vision Association is formulated
Sensor and camera testing standard) on the basis of, devise one contain can measured data and measured parameter fitness function,
A kind of new imaging sensor key parameter test method is proposed in conjunction with particle cluster algorithm.
First according to EMVAStandard1288 standards, light field and dark-field manner are carried out under 30 different time for exposure
Exposure, obtains 30 groups of light field gray value variances, light field gray value mean value, details in a play not acted out on stage, but told through dialogues gray value mean value.
The total searching times of particle cluster algorithm are 600, system gain K, dark current μI, initial dark signal varianceComposition
Three dimensional particles randomly generate 400 particles as initial population.After particle generates, set suitable set by S3 in claim 1
Response function calculates the fitness function value of each individual, judges whether the end condition for reaching preset particle cluster algorithm, such as
Fruit is not to enter the position about particle for otherwise entering step and being carried out according to the fitness value in particle cluster algorithm in algorithm, speed
The update of degree, gradually evolutionary search, until meeting algorithm end condition, the highest particle of fitness value is exactly imaging sensor
The inversion result of system gain, dark current, initial dark signal variance.
Claims (1)
1. a kind of test method of the imaging sensor critical performance parameters based on particle cluster algorithm, which is characterized in that include
Following steps：
(1) operation is exposed to imaging sensor, takes n different time for exposure, then acquire n frame light field data and n respectively
Frame details in a play not acted out on stage, but told through dialogues data calculate light field gray value variance according to the requirements of EMVA Standard 1288Light field gray value mean value
μy, details in a play not acted out on stage, but told through dialogues gray value μydark；
(2) particle cluster algorithm inverting is carried out to be as follows：
(2.1) by the system gain K of imaging sensor, dark current μI, initial dark signal varianceForm three dimensional particles；
(2.2) set particle individual adaptation degree function as：
Wherein,It is light field gray value variance, K is system gain, μIFor dark current, texpFor time for exposure, σqFor quantizing noise；
(2.3) optimal estimation of system gain, dark current, initial dark signal variance is obtained according to the optimizing flow of particle cluster algorithm
Value.
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Citations (2)
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| CN103698682A (en) * | 2013-12-20 | 2014-04-02 | 中国空间技术研究院 | CMOS (Complementary Metal-Oxide-Semiconductor Transistor) image sensor testing device on basis of FPGA (Field Programmable Gate Array) technology |
| CN103914831A (en) * | 2014-03-10 | 2014-07-09 | 西安电子科技大学 | Two-dimensional dual-threshold SAR image segmentation method based on quantum particle swarm optimization |
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| JP2010034703A (en) * | 2008-07-25 | 2010-02-12 | Fujifilm Corp | Method and equipment for inspecting image sensor |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103698682A (en) * | 2013-12-20 | 2014-04-02 | 中国空间技术研究院 | CMOS (Complementary Metal-Oxide-Semiconductor Transistor) image sensor testing device on basis of FPGA (Field Programmable Gate Array) technology |
| CN103914831A (en) * | 2014-03-10 | 2014-07-09 | 西安电子科技大学 | Two-dimensional dual-threshold SAR image segmentation method based on quantum particle swarm optimization |
Non-Patent Citations (2)
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| CCD光电参数测试系统的研制;周跃 等;《红外与激光工程》;20141031;第43卷(第10期);第3451-3456页 * |
| CCD芯片性能参数测量系统;许宏涛 等;《仪器仪表学报》;20110630;第32卷(第6期);第271-275页 * |
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