CN106657803B - Electro-optic theodolite high speed camera automatic explosion method - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/71—Circuitry for evaluating the brightness variation
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
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Abstract
Electro-optic theodolite high speed camera automatic explosion method, it is related to field of photoelectric technology, solve the problems, such as the automatic explosion method of the prior art cannot achieve high speed camera is carried out in the continually changing situation of target background illumination it is with an automatic light meter, the present invention use image histogram feature HF function automatic explosion method, for background illumination quickly, wide variation in the case where to high speed camera carry out auto-exposure control.Image histogram characteristic function method can provide higher information entropy in a short time；With directly use image information entropy as the method for evaluation criterion compared with.The present invention judges that compensation direction and step-length reduce auto exposure system search time by HF function.The present invention can effectively improve the accuracy and stability of high speed camera automatic exposure using the automatic explosion method of image histogram characteristic function, provide more image detail information for subsequent image identification and image trace.
Description
Technical field
The present invention relates to field of photoelectric technology, and in particular to a kind of electro-optic theodolite high speed camera automatic explosion method.
Background technique
With the rapid development of cmos image sensor (CMOS Image Sensor, CIS) technology, CIS system is in military affairs
It is all widely used with civil field.High speed camera is one kind of CIS system, and frame per second is common CIS system (example
Several times to thousands of times such as: NTSC 30fps or PAL 25fps) are even higher, rely on this feature, and high speed camera is answered extensively
For recording specified moment state or all processes in target motion process, to obtain accurately time, spatial information, it is
The characteristics of motion for studying high speed phenomenon provides reliable foundation.
High speed camera generallys use highly sensitive imaging sensor, to observed object brightness and background illumination require compared with
Height, the high speed camera of early stage is typically employed under conditions of can manually providing good illumination, such as industrial detection and sportsman
Motion state observation etc..Currently, with to the wider demand of high-speed target Kinematic, high speed camera starts to be applied to
Under the conditions of natural light, such as electro-optic theodolite.But the dynamic range of illumination is much higher than the dynamic range of CIS, high speed in nature
Camera shooting image be particularly easy to be saturated, and cause lose great amount of images details, no matter subsequent eye-observation or image
Tracker differentiates that characteristics of image will be all greatly affected, to influence the tracking performance of electro-optic theodolite etc..Therefore, of the invention
Electro-optic theodolite is had studied emphatically how rapidly to exit over-exposed or under-exposure shape in the task of execution with high speed camera
State, and accurate exposure value is found, it is the image that subsequent focusing and target following are provided with good depth of exposure.
Automatic exposure (Auto Exposure, AE) has become a key factor for influencing digital camera image quality.
By the time for exposure of adjust automatically camera, the overexposure or under-exposure phenomenon of camera is can be effectively reduced in auto exposure system,
Maximize the detailed information for obtaining image.
Currently, there is many researchs from average brightness value, image brightness histogram, comentropy, dct transform, mathematics both at home and abroad
Iteration and image co-registration scheduling algorithm study automatic exposure.But it is wherein most of only for the number for shooting static picture
Code camera, or work rarely have for high speed camera in the video camera of nominal frequencies in the continually changing feelings of target background illumination
Research with an automatic light meter is carried out under condition.
Summary of the invention
The present invention be solve the prior art automatic explosion method cannot achieve to high speed camera target background illumination not
Problem with an automatic light meter is carried out in the case where disconnected variation, a kind of electro-optic theodolite high speed camera automatic explosion method is provided.
Electro-optic theodolite high speed camera automatic explosion method, this method are realized by following steps:
Step 1: being analyzed using brightness of image of the HF function to input；Concrete analysis process are as follows:
HF function is defined as the image that brightness value in the image histogram after normalization is higher than luminance threshold value th
The sum of histogram normalized function；
The HF function are as follows:
High speed camera captured image brightness is analyzed using four parameters, four parameters are respectively brightness door
HF functional value H_mean when limit value th is average brightness value, HF functional value H_ when luminance threshold value th is average brightness value half
The functional value H_twice and calculated value H_diff of HF, the calculating when half, luminance threshold value th are two times of average brightness value
The value of value H_diff is the contrast that reaction obtains bright area and dark areas in image；
Step 2: exposure coarse adjustment and exposure accurate adjustment, realize high speed camera automatic exposure；
In the process of exposure coarse adjustment are as follows:
A, whether the functional value H_twice of HF is more than or equal to overexposure when judging luminance threshold value th for two times of average brightness value
Optical gate limit value α, if so, step b is executed, if not, executing c；
B, reduce time for exposure, return step a；
C, whether HF functional value H_half is more than or equal to under-exposure when judging luminance threshold value th for average brightness value half
Threshold value returns to a if so, increasing the time for exposure, if not, executing step d；
D, it is exposed accurate adjustment；
Expose the process of accurate adjustment are as follows:
A, judge HR(k) whether it is more than or equal to exposure point threshold value γ, if so, calculating compensation step-length using fuzzy rule
Cp, if not, executing step B；
B, judge Hm(k) whether it is greater than 0, the HmIt (k) is the H_half of the H_half value of kth width image and k-1 width image
The difference of value, the Hm(k)=H_half (k)-H_half (k-1)；
If so, C is thened follow the steps, if not, executing step D；
C, step-length C will be compensatedpValue reduces N times, it may be assumed that Cp=Cp/ N, while with the exposure compensating step-length of -2 width image of kth work
To be formulated are as follows: E (k)=E (k-2) × C with reference to compensatingP；
Judge CpWhether θ is less than or equal to, if it is, keeping the exposure compensating step-length of -2 width image of kth constant, it may be assumed that E
(k)=E (k-2), if not, E (k)=E (k-1) × (1+CP)；
D, E (k)=E (k-2) × (1+CP)；
In above-mentioned steps A,
HR(k) the first width image H for kth width image and by fuzzy rule compensationO(0) ratio of overexposure pixel；HR
(k) estimation function are as follows:
H in formulaOIt (k) is the overexposure light pixel summation of kth width image；
Compensation step-length C is calculated using fuzzy rulepDetailed process are as follows:
HF functional value H_mean and calculating when using triangular form subordinating degree function by luminance threshold value th for average brightness value
Value H_diff is summarized as the triangular form subordinating degree function of five kinds of degree respectively；
The offset that C (i, j) is the time for exposure is set, the time for exposure direction of adjustment is indicated with sign, when λ is exposure
Between adjusting step；
The triangular form subjection degree that u (i, j) is fuzzy rule is defined, is formulated are as follows:
In formula, U (i) and U (j) are respectively calculated value H_diff and luminance threshold value th HF functional value when being average brightness value
The subordinating degree function of H_mean；
The compensation step-length CpIt is obtained by following formula:
Then the time for exposure of kth width image, it is formulated are as follows:
E (k)=E (k-1) × CP。
Beneficial effects of the present invention: the present invention is using image histogram feature (Histogram Feature, HF) function
Automatic explosion method, for background illumination quickly, wide variation in the case where to high speed camera carry out auto-exposure control.
Method of the present invention can complete the brightness measurement of a frame image within the 2ms time and carry out to the time for exposure
Adjustment, directly uses the luminance information of image as the side of evaluation criterion relative to average brightness value method and mathematical iterations method etc.
Method, image histogram characteristic function method can provide higher information entropy in a short time；With directly use image information
Entropy compares as the method for evaluation criterion,
Method of the present invention can judge that compensation direction reduces auto exposure system with step-length and searches by HF function
The rope time.Experiment shows that can effectively improve high speed camera using the automatic explosion method of image histogram characteristic function exposes automatically
The accuracy and stability of light provide more image detail information for subsequent image identification and image trace.
Detailed description of the invention
Fig. 1 is the system construction drawing of electro-optic theodolite high speed camera automatic explosion method of the present invention；
Fig. 2 is the flow chart of electro-optic theodolite high speed camera automatic explosion method of the present invention.
Fig. 3 is the subordinating degree function of HF function in electro-optic theodolite high speed camera automatic explosion method of the present invention
Schematic diagram.
Specific embodiment
Specific embodiment one illustrates present embodiment in conjunction with Fig. 1 to Fig. 3, and electro-optic theodolite is exposed automatically with high speed camera
Light method is divided into two steps,
The first step is the measurement of brightness of image: Fig. 1 shows the overall process of high speed camera auto exposure system.
Detailed process are as follows:
Image is shown to user by Camera Link by high speed camera, after camera executes automatic exposure, in order to reduce
System-computed amount, the image head currently obtained analyze the brightness for obtaining image by HF function.
Grey level histogram (Histogram) is the function of gray level, the pixel with every kind of gray level in its presentation image
Number, reflect image in every kind of gray scale occur frequency.Input picture is set as I (x, y), there is xy pixel, gray level
For L, h (r) is the grey level histogram of I (x, y): the grey level histogram h (r) is formulated are as follows:
Wherein,
Grey level histogram h (r) is normalized, is obtained:
Although grey level histogram can accurately indicate all pixels point in image in the distribution situation of every kind of gray level,
It is that it is too sensitive for brightness slight change and influence of noise in image, when judging brightness of image for machine, often
It will lead to evaluation function concussion.In order to improve the brightness robustness of measurement target and background, HF function is defined as by normalizing
Brightness value is higher than the sum of the image histogram normalized function of luminance threshold value th in image histogram after change；
The HF function are as follows:
High speed camera captured image is measured using four parameters in the present embodiment, wherein three pass through HF
The parameter that function obtains is denoted as: H_mean, H_half and H_twice, they are respectively that luminance threshold value th is average brightness
HF functional value and luminance threshold value th when the functional value of HF, luminance threshold value th are average brightness value half when value are averagely bright
HF functional value at two times of angle value.4th parameter H_diff is calculated value, is formulated are as follows:
Second step is time for exposure adjustment.The automatic explosion method that Fig. 2 shows that present embodiment proposes is roughly divided into exposure
Light coarse adjustment and exposure accurate adjustment.
In exposure coarse tuning stage, the brightness of image of acquisition is extracted first, and four HF functional values of the sense of access.With
Afterwards, use following judgment modes that can expose the process of coarse adjustment with trigger exposure coarse adjustment are as follows:
A, whether the functional value H_twice of HF is more than or equal to overexposure when judging luminance threshold value th for two times of average brightness value
Optical gate limit value α, if so, step b is executed, if not, executing c；
B, reduce time for exposure, return step a；
C, whether HF functional value H_half is more than or equal to under-exposure when judging luminance threshold value th for average brightness value half
Threshold value returns to a if so, increasing the time for exposure, if not, executing step d；
D, it is exposed accurate adjustment；The process of the exposure accurate adjustment are as follows:
In the exposure accurate adjustment stage, HR(k) kth width image and the first width image H by fuzzy rule compensation are indicatedO(0) mistake
The ratio of exposing pixels point.HR(k) estimation function are as follows:
Wherein HO(k) the overexposure light pixel summation of kth width image is represented.In the present embodiment, the pixel of overexposure
It is defined as the pixel more than maximum brightness value 95%, while exposure point threshold value γ is preset as 0.2.
Image or H headed by the image of acquisitionR(k) when being more than exposure point threshold value γ,
The direction and compensation progress that the auto exposure system of present embodiment compensate the time for exposure by fuzzy rule
H_mean and H_diff are summarized as 5 kinds of journeys of VS, S, M, B and VB using triangular form subordinating degree function first by judgement respectively
Degree, for these subordinating degree functions, proposes 12 fuzzy rules pair
Exposure value compensates, and C (i, j) represents the offset of time for exposure, and sign indicates the side of time for exposure adjustment
To λ is time for exposure adjusting step.
The triangular form subjection degree that u (i, j) is fuzzy rule is defined, is indicated with following formula are as follows:
U (i) and U (j) is respectively the subordinating degree function of H_diff and H_mean.
Compensation step-length can be obtained by formula:
Then the time for exposure of K width image is by Shi Ke get:
E (k)=E (k-1) × CP (9)
E (k) represents the time for exposure of kth width image in formula.
Work as HO(k) when being no more than threshold value, then continue to judge Hm(k)。
Hm(k) difference of the H_half value of kth width image and the H_half minimum value of k-1 width image, function such as formula are indicated
It is shown:
Hm(k)=H_half (k) (k-1) (10)-H_half
Work as Hm(k) < 0 when, the time for exposure of kth width image compensates using the exposure value of -1 width image of kth as reference,
As shown in formula (10).
Work as Hm(k) > 0 when, then Cp value is reduced N times, while using the exposure value of -2 width image of kth as reference, such as formula institute
Show:
E (k)=E (k-2) × CP (12)
Keep the exposure value of -2 width image of kth constant if Cp is less than threshold value θ simultaneously, as shown in formula:
E (k)=E (k-2) (13)
Five kinds of degree that triangular form subordinating degree function is defined in present embodiment are respectively as follows: very small VS, small S, medium M,
Big B and very big VB, for the triangular form subordinating degree function of five kinds of degree, using following 12 fuzzy rules to the time for exposure
It is to compensate；
Rule 1: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value
When H_mean is very small VS, offset C (1,1) is -2 λ；
Rule 2: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value
When H_mean is small S, offset C (1,2) is+2 λ；
Rule 3: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value
H_mean is M, and offset C (1,3) is+4 λ；
Rule 4: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value
When H_mean is big B, offset C (Isosorbide-5-Nitrae) is+3 λ；
Rule 5: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value
When H_mean is very big VB, offset C (1,5) is+λ；
Rule 6: the value as calculated value H_diff is set as small S and when luminance threshold value th is average brightness value H_mean
When for very small VS, offset C (2,1) is-λ；
Rule 7: the value as calculated value H_diff is set as small S and when luminance threshold value th is average brightness value H_mean
When for small S, offset C (2,2) is+λ；
Rule 8: the value as calculated value H_diff is set as small S and when luminance threshold value th is average brightness value H_mean
When for medium M, offset C (2,3) is+3 λ；
Rule 9: the value as calculated value H_diff is set as small S and when luminance threshold value th is average brightness value H_mean
When for big B, offset C (2,4) is+2 λ；
Rule 10: the value as calculated value H_diff is set as small S and when luminance threshold value th is average brightness value H_
When mean is very big VB, offset C (2,5) is λ；
Rule 11: the value as calculated value H_diff is set as medium M and when luminance threshold value th is average brightness value H_
When mean is medium M, offset C (3,3) is λ；
Rule 12: other situations, compensating is 0.
In exposure coarse adjustment described in present embodiment, α, β and time for exposure reduce with the amplitude that increases to preset
Fixed value.At the same time, it is also necessary to judge whether the time for exposure has reached the minimum or highest time for exposure of high speed camera.
After needing beyond the minimum or highest time for exposure time for exposure of system detection to camera, indicate to be directed to current illumination condition,
Auto exposure system has been unable to control camera and has well been imaged, and needs to terminate auto-exposure control.
Method described in present embodiment passes through exposure coarse adjustment first and is adjusted on a large scale to the time for exposure of camera,
And whether the bias light illumination of real-time monitoring image occurs more than preset range variation, once background transition change, then pass through mould
Paste rule again calculates exposure bias value, if background illumination variation on the contrary is smaller, by the method for variable step to exposure
Light carries out accurate adjustment, to guarantee the precision of high speed camera light modulation.
Claims (5)
1. electro-optic theodolite high speed camera automatic explosion method, characterized in that this method is realized by following steps:
Step 1: being analyzed using brightness of image of the HF function to input；Concrete analysis process are as follows:
HF function is defined as the image histogram that brightness value in the image histogram after normalization is higher than luminance threshold value th
The sum of figure normalized function；
The HF function are as follows:
In formula, L is image gray levels, and th is luminance threshold value, using four parameters to the brightness of high speed camera captured image into
Row analysis, four parameters be respectively luminance threshold value th be average brightness value when HF functional value H_mean, luminance threshold value
HF functional value H_half when th is average brightness value half, the functional value H_ of HF when luminance threshold value th is two times of average brightness value
Twice and calculated value H_diff, the value of the calculated value H_diff are pair that reaction obtains bright area and dark areas in image
Degree of ratio；
Step 2: exposure coarse adjustment and exposure accurate adjustment, realize high speed camera automatic exposure；
In the process of exposure coarse adjustment are as follows:
A, whether the functional value H_twice of HF is more than or equal to overexposure optical gate when judging luminance threshold value th for two times of average brightness value
Limit value α, if so, step b is executed, if not, executing c；
B, reduce time for exposure, return step a；
C, whether HF functional value H_half is more than or equal to under-exposure thresholding when judging luminance threshold value th for average brightness value half
Value β returns to a if so, increasing the time for exposure, if not, executing step d；
D, it is exposed accurate adjustment；
Expose the process of accurate adjustment are as follows:
A, judge HR(k) whether it is more than or equal to exposure point threshold value γ, if so, calculating compensation step-length C using fuzzy rulep, such as
Fruit is no, executes step B；
B, judge Hm(k) whether it is greater than 0, the HmIt (k) is the H_half value of kth width image and the H_half value of k-1 width image
Difference, the Hm(k)=H_half (k)-H_half (k-1)；
If so, C is thened follow the steps, if not, executing step D；
C, step-length C will be compensatedpValue reduces N times, it may be assumed that Cp=Cp/ N, while using the exposure compensating step-length of -2 width image of kth as ginseng
It examines and compensates, be formulated are as follows: E (k)=E (k-2) × CP；
Judge CpWhether threshold value θ is less than or equal to, if it is, keeping the exposure compensating step-length of -2 width image of kth constant, it may be assumed that E
(k)=E (k-2), if not, E (k)=E (k-1) × (1+CP)；
D, E (k)=E (k-2) × (1+CP)；
In above-mentioned steps A,
HR(k) the first width image H for kth width image and by fuzzy rule compensationO(0) ratio of overexposure pixel；HR(k)
Estimation function are as follows:
H in formulaOIt (k) is the overexposure light pixel summation of kth width image；
Compensation step-length C is calculated using fuzzy rulepDetailed process are as follows:
HF functional value H_mean and calculated value H_ when using triangular form subordinating degree function by luminance threshold value th for average brightness value
Diff is summarized as the triangular form subordinating degree function of five kinds of degree respectively；
The offset that C (i, j) is the time for exposure is set, the time for exposure direction of adjustment indicates that λ is time for exposure tune with sign
Synchronizing is long；
The triangular form subjection degree that u (i, j) is fuzzy rule is defined, is formulated are as follows:
Definition
In formula, U (i) and U (j) are respectively calculated value H_diff and luminance threshold value th HF functional value H_ when being average brightness value
The subordinating degree function of mean；
The compensation step-length CpIt is obtained by following formula:
Then the time for exposure of kth width image, it is formulated are as follows:
E (k)=E (k-1) × CP。
2. electro-optic theodolite according to claim 1 high speed camera automatic explosion method, which is characterized in that step 1
In,
Input picture is set as I (x, y), there is xy pixel, h (r) is the grey level histogram of I (x, y): the grey level histogram
H (r) is formulated are as follows:
Wherein,
Grey level histogram h (r) is normalized, is obtained:
Norm (r)=h (r)/xy and
3. electro-optic theodolite according to claim 1 high speed camera automatic explosion method, which is characterized in that the calculating
Value H_diff is formulated are as follows:
H_diff=MIN | H_twice-H_mean |,
|H_mean-H_half|}。
4. electro-optic theodolite according to claim 1 high speed camera automatic explosion method, which is characterized in that
The pixel summation H of the overexposure of the kth width imageO(k) it is the pixel more than maximum brightness value 95%, and defines
Exposure point threshold value γ is set as 0.2.
5. electro-optic theodolite according to claim 1 high speed camera automatic explosion method, which is characterized in that define triangle
Five kinds of degree of type subordinating degree function are respectively as follows: very small VS, small S, medium M, big B and very big VB, for five kinds of degree
Triangular form subordinating degree function, be to compensate to the time for exposure using following 12 fuzzy rules；
Rule 1: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value H_
When mean is very small VS, offset C (1,1) is -2 λ；
Rule 2: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value H_
When mean is small S, offset C (1,2) is+2 λ；
Rule 3: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value H_
Mean is M, and offset C (1,3) is+4 λ；
Rule 4: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value H_
When mean is big B, offset C (Isosorbide-5-Nitrae) is+3 λ；
Rule 5: the value as calculated value H_diff is set as very small VS and when luminance threshold value th is average brightness value H_
When mean is very big VB, offset C (1,5) is+λ；
Rule 6: setting the value for working as calculated value H_diff as small S and is non-when luminance threshold value th is average brightness value H_mean
When normal small VS, offset C (2,1) is-λ；
Rule 7: setting the value for working as calculated value H_diff as small S and is small when luminance threshold value th is average brightness value H_mean
When S, offset C (2,2) is+λ；
Rule 8: the value as calculated value H_diff is set as small S and when luminance threshold value th is during average brightness value H_mean is
When equal M, offset C (2,3) is+3 λ；
Rule 9: setting the value for working as calculated value H_diff as small S and is big when luminance threshold value th is average brightness value H_mean
When B, offset C (2,4) is+2 λ；
Rule 10: the value as calculated value H_diff is set as small S and when luminance threshold value th is that average brightness value H_mean is
When very big VB, offset C (2,5) is λ；
Rule 11: the value as calculated value H_diff is set as medium M and when luminance threshold value th is average brightness value H_mean
When for medium M, offset C (3,3) is λ；
Rule 12: other situations, compensating is 0.
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| CN107289902A (en) * | 2017-06-20 | 2017-10-24 | 中国科学技术大学 | Binocular high-speed, high precision theodolite based on image recognition with tracking |
| CN108174114B (en) * | 2017-12-08 | 2020-06-30 | 上海集成电路研发中心有限公司 | Entropy calculation device and entropy calculation method |
| CN110602414B (en) * | 2019-09-19 | 2021-04-27 | 天地伟业技术有限公司 | Camera automatic exposure method based on ambient brightness and image information entropy |
| CN214202002U (en) * | 2020-08-03 | 2021-09-14 | 神盾股份有限公司 | Display device with fingerprint sensing function |
| CN115578662A (en) * | 2022-11-23 | 2023-01-06 | 国网智能科技股份有限公司 | Unmanned aerial vehicle front-end image processing method, system, storage medium and equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013250A (en) * | 2006-01-30 | 2007-08-08 | 索尼株式会社 | Exposure control apparatus and image pickup apparatus |
| CN100435562C (en) * | 2006-12-28 | 2008-11-19 | 上海交通大学 | Automatic explosion method based on multi-area partition and fuzzy logic |
| CN101399924A (en) * | 2007-09-25 | 2009-04-01 | 展讯通信（上海）有限公司 | Automatic exposure method and device based on brightness histogram |
| CN102801920A (en) * | 2012-07-25 | 2012-11-28 | 中国科学院长春光学精密机械与物理研究所 | Sensorless continuous automatic exposure time adjusting and controlling device of camera |
| CN103237175A (en) * | 2013-04-17 | 2013-08-07 | 中国科学院西安光学精密机械研究所 | Automatic exposure method of digital camera based on human visual characteristics |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8493500B2 (en) * | 2010-10-27 | 2013-07-23 | Apple Inc. | Auto exposure blowout prevention |
-
2016
- 2016-12-26 CN CN201611214182.8A patent/CN106657803B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013250A (en) * | 2006-01-30 | 2007-08-08 | 索尼株式会社 | Exposure control apparatus and image pickup apparatus |
| CN100435562C (en) * | 2006-12-28 | 2008-11-19 | 上海交通大学 | Automatic explosion method based on multi-area partition and fuzzy logic |
| CN101399924A (en) * | 2007-09-25 | 2009-04-01 | 展讯通信（上海）有限公司 | Automatic exposure method and device based on brightness histogram |
| CN102801920A (en) * | 2012-07-25 | 2012-11-28 | 中国科学院长春光学精密机械与物理研究所 | Sensorless continuous automatic exposure time adjusting and controlling device of camera |
| CN103237175A (en) * | 2013-04-17 | 2013-08-07 | 中国科学院西安光学精密机械研究所 | Automatic exposure method of digital camera based on human visual characteristics |
Non-Patent Citations (2)
| Title |
|---|
| Multiple templates auto exposure control based on luminance histogram for onboard camera;Tao Jiang等;《2011 IEEE International Conference on Computer Science and Automation Engineering》;20110704;237-241 * |
| 一种基于亮度直方图的自动曝光控制方法;杨海涛等;《光学学报》;20070515;第27卷(第5期);841-847 * |
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