CN103188446A - Exposure method of video camera - Google Patents
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- CN103188446A CN103188446A CN2012105046727A CN201210504672A CN103188446A CN 103188446 A CN103188446 A CN 103188446A CN 2012105046727 A CN2012105046727 A CN 2012105046727A CN 201210504672 A CN201210504672 A CN 201210504672A CN 103188446 A CN103188446 A CN 103188446A
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Abstract
The invention is applicable to the field of communication and provides an exposure method of a video camera. The exposure method of the video camera comprises the following steps of: detecting intensity of ambient light in exposure; if the intensity exceeds a threshold value, determining as day, and adjusting target light intensity and a light intensity average value in a formula 2.2 to be day target light intensity and a day light intensity average value; and if the light intensity is lower than a threshold value, determining as night, and adjusting the target light intensity and the light intensity average value to be night target light intensity and a night light intensity average value. The technical scheme provided by the invention has the advantages of good spatial brightness uniformity and uniform image frame.
Description
Technical field
The invention belongs to the shooting field, relate in particular to a kind of exposure method of video camera.
Background technology
Automatic exposure (AUTO EXPOSURE, AE), Automatic white balance (AUTO WHITEBALANCE, AWB) algorithm is the key technology of field of cameras, is described as the jewel of field of cameras; (Digital Signal Processing, DSP) technology limitation, AE, AWB core technology are mainly grasped abroad in some monopoly enterprise's hands for many years to be subjected to image sensor and image processing Digital Signal Processing.Over nearly 3 years, China's video monitoring obtains extensive depth and uses, greatly promote native country image enterprise-like corporation enthusiasm, especially original monopolization image processing general layout has thoroughly been overturned in the development of high-definition camera technology, the leading enterprise in domestic monitoring field captures AE, AWB technology in succession, and Chinese rig camera becomes global core force rapidly.
Domestic safe city monitoring has the characteristics of China itself, the supporting difference of urban development scale and facility is big, lighting environment is generally undesirable, the infrared night vision product mainly needs to solve two problems, the one, ensure in the night visual range scope, video camera brightness remains unchanged substantially, i.e. the spatial brightness homogeneity question; The 2nd, prevent " flashlight " effect, namely middle bright, the edge is dark, causes image frame inhomogeneous, i.e. image plane brightness uniformity problem.
Summary of the invention
The purpose of the embodiment of the invention is to provide a kind of exposure method of video camera, and it solves spatial brightness uniformity and the inhomogeneous problem of image frame of prior art.
The embodiment of the invention is achieved in that on the one hand, and a kind of exposure method of video camera is provided, and described method comprises:
The intensity of ambient light when detecting exposure;
Intensity surpasses threshold value as described, confirms as daytime, with the object brightness in the formula 2.2 and average brightness be adjusted to daytime object brightness and daytime average brightness, according to described daytime object brightness and described daytime average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to described formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust;
Intensity is lower than threshold value as described, is defined as night, with the object brightness in the described formula 2.2 and average brightness be adjusted to night object brightness and night average brightness, according to described night object brightness and described night average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to described formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust;
Described formula 2.1 is specially:
Av+Tv=Lv+Sv 2.1
Wherein,
Av: lens aperture, Tv: time for exposure, Sv: the gain of imageing sensor; Lv: image brightness;
Described formula 2.2 is specially:
DeltaEV=AE_MULTIPLE*(log_2(AePreviewAverageLuma)—log_2(AeTargetLuma))；2.2
AePreviewAverageLuma is: average brightness; Ae Target Luma is: object brightness; AE_MULTIPLE is constant.
Optionally, described daytime average brightness computational methods be:
The image of current image frame is divided into grid; Average brightness is:
AePreviewAverageLuma=Luma(i，j)*weight(i，j)/(WINVC*WINHC)2.3
Wherein, (i j) is raster brightness mean value to Luma, and (i j) is the raster brightness weight to weight; WINVC is described grid grid number in the vertical direction, and WINHC is that described grid is at the grid number of vertical direction.
Weight (i, j) matrix of luminance weights (daytime) is specially:
{10,10,10,10,10,10,10,10,10,10,10,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,10,10,10,10,10,10,10,10,10,10,10}。
Optionally, described night average brightness computational methods be:
The image of current image frame is divided into grid; Average brightness is:
AePreviewAverageLuma=Luma(i，j)*weight(i，j)/(WINVC*WINHC)2.3
Wherein, (i j) is raster brightness mean value to Luma, and (i j) is the raster brightness weight to weight; WINVC is this grid grid number in the vertical direction, and WINHC is that this grid is at the grid number of vertical direction.
Weight (i, j) matrix of luminance weights be night the luminance weights matrix be:
{1,1,1,1,1,1,1,1,1,1,1,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,1,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,1,1,1,1,1,1,1,1,1,1,1}。
In embodiments of the present invention, technical scheme provided by the invention has taken into full account the factor of ambient light, under different environment, select different object brightnesses and average brightness to adjust the exposure of camera, so it has spatial brightness good uniformity and the uniform advantage of image frame.
Description of drawings
Fig. 1 is the flow chart of the exposure method of a kind of video camera provided by the invention;
Fig. 2 is the schematic diagram of grid provided by the invention.
Embodiment
In order to make purpose of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explaining the present invention, and be not used in restriction the present invention.
Usually video camera automatic exposure algorithm principle is exactly the balance of assurance formula 2.1.
Av+Tv=Lv+Sv 2.1
Wherein,
Av: lens aperture, Tv: time for exposure, Sv: the gain of imageing sensor; Lv: image brightness object brightness Ae Target Luma is according to environment set, be set point, when image brightness changes, calculate average brightness Ae Preview Average Luma according to image brightness Lv, the changing value of Lv is: image brightness difference DeltaLv, be the difference of two adjacent images frame Lv, DeltaEV can calculate by through type 2.2, and DeltaEV is the difference of the expression two adjacent images frame Lv that calculates according to the image brightness (measuring) of current image frame; Need to prove that DeltaEV only is calculated value, itself and DeltaLv are inequality.AE_MULTIPLE is a constant, and concrete numerical value can be 1024.
DeltaEV=AE_MULTIPLE*(log_2(AePreviewAverageLuma)—log_2(AeTargetLuma)) 2.2
For the brightness Lv that makes picture frame constant substantially, we must adjust Av, Tv and Sv, make that DeltaLv is zero, thereby the Lv of maintenance current image frame and the Lv of next picture frame are basic identical, and the difference of the two adjacent images frame Lv that DeltaEV is us to be calculated according to the Lv of current image frame, so the present invention adjusts Av, Tv and Sv according to DeltaEV, making DeltaLv is zero, and making formula 2.1 still keep balance can reach DeltaLv is zero effect substantially.Because being the average brightness of foundation exposure object brightness and present frame, calculates DeltaEV, so adjust Av, Tv and Sv according to DeltaEV, just can make according to the Lv of the Lv of formula 2.1 next frame that calculates and present frame constant substantially, thereby reach maintenance present frame and the unconverted substantially advantage of next frame brightness.
The specific embodiment of the invention provides a kind of exposure method of video camera, and this method is finished by video camera, and this method comprises as shown in Figure 1:
The intensity of ambient light when S11, detection exposure;
S12, surpass threshold value as intensity, confirm as daytime, with the object brightness in 2.2 and average brightness be adjusted to daytime object brightness and daytime average brightness, according to daytime object brightness and daytime average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust.
S13, be lower than threshold value as intensity, be defined as night, with the object brightness in 2.2 and average brightness be adjusted to night object brightness and night average brightness, according to night object brightness and night average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust.
Need to prove, according to DeltaEV adjust Av, Tv and Sv concrete grammar can for:
As DeltaEV be on the occasion of, illustrate that then the Lv of next frame image will become greatly, then Av or Tv are increased, Sv is constant, the Lv after the adjustment that calculates according to formula 2.1 just becomes big like this, thereby improves image brightness.Be negative value as DeltaEV, illustrate that then the Lv of next frame image will diminish, then Av or Tv are increased for a short time, Sv is constant, and the Lv after the adjustment that calculates according to formula 2.1 has just diminished like this, thereby lowers image brightness.
The method that the specific embodiment of the invention provides is when exposure, taken into full account the factor of ambient light, under different environment, select different object brightnesses and average brightness to adjust the exposure of camera, and adjust the image brightness of next frame according to the brightness of current image frame, so image has spatial brightness good uniformity and the uniform advantage of image frame.
Optionally, above-mentioned daytime average brightness computational methods can for:
Current image frame (i.e. the nearest picture frame that obtains before the exposure) is divided into grid (this grid as shown in Figure 2, in Fig. 2, WINH represents the pixel number of the every lattice of vertical direction, and WINW represents the pixel number of the every lattice of horizontal direction);
AePreviewAverageLuma=Luma(i，j)*weight(i，j)/(WINVC*WINHC)(2.3)
Wherein, (i j) is raster brightness mean value to Luma, and it obtains by measuring current image frame, and (i j) is image brightness Lv for the general performance of raster brightness mean value to this Luma; (i j) is the raster brightness weight to weight; WINVC is this grid grid number in the vertical direction, and WINHC is that this grid is at the grid number of vertical direction.
Weight (i, j) matrix of luminance weights (daytime) is specifically as follows:
{10,10,10,10,10,10,10,10,10,10,10,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,10,10,10,10,10,10,10,10,10,10,10}
Optionally, above-mentioned night average brightness computational methods and daytime difference only be weight this moment (i, j) matrix of luminance weights is luminance weights matrix at night, is specifically as follows:
{1,1,1,1,1,1,1,1,1,1,1,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,1,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,1,1,1,1,1,1,1,1,1,1,1}
Above-mentioned by daytime the luminance weights matrix and night the luminance weights matrix can take into full account the variation at daytime and night, make image have spatial brightness good uniformity and the uniform advantage of image frame.
It should be noted that in above-described embodiment that each included unit is just divided according to function logic, but is not limited to above-mentioned division, as long as can realize corresponding function; In addition, the concrete title of each functional unit also just for the ease of mutual differentiation, is not limited to protection scope of the present invention.
In addition, one of ordinary skill in the art will appreciate that all or part of step that realizes in the various embodiments described above method is to instruct relevant hardware to finish by program, corresponding program can be stored in the computer read/write memory medium, described storage medium is as ROM/RAM, disk or CD etc.
The above only is preferred embodiment of the present invention, not in order to limiting the present invention, all any modifications of doing within the spirit and principles in the present invention, is equal to and replaces and improvement etc., all should be included within protection scope of the present invention.
Claims (3)
1. the exposure method of a video camera is characterized in that, described method comprises:
The intensity of ambient light when detecting exposure;
Intensity surpasses threshold value as described, confirms as daytime, with the object brightness in the formula 2.2 and average brightness be adjusted to daytime object brightness and daytime average brightness, according to described daytime object brightness and described daytime average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to described formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust;
Intensity is lower than threshold value as described, is defined as night, with the object brightness in the described formula 2.2 and average brightness be adjusted to night object brightness and night average brightness, according to described night object brightness and described night average brightness calculate DeltaEV; Adjust Av, Tv and Sv according to DeltaEV, and calculate Lv ' after the adjustment according to described formula 2.1, when the difference of Lv ' and the Lv of current image frame is zero, finish to adjust;
Described formula 2.1 is specially:
Av+Tv=Lv+Sv 2.1
Wherein,
Av: lens aperture, Tv: time for exposure, Sv: the gain of imageing sensor; Lv: image brightness;
Described formula 2.2 is specially:
DeltaEV=AE_MULTIPLE*(log_2(AePreviewAverageLuma)—log_2(AeTargetLuma))；2.2
AePreviewAverageLuma is: average brightness; Ae Target Luma is: object brightness; AE_MULTIPLE is constant.
2. method according to claim 1 is characterized in that, described daytime, the computational methods of average brightness were:
The image of current image frame is divided into grid; Average brightness is:
AePreviewAverageLuma=Luma(i，j)*weight(i，j)/(WINVC*WINHC)2.3
Wherein, (i j) is raster brightness mean value to Luma, and (i j) is the raster brightness weight to weight; WINVC is described grid grid number in the vertical direction, and WINHC is that described grid is at the grid number of vertical direction.
Weight (i, j) matrix of luminance weights (daytime) is specially:
{10,10,10,10,10,10,10,10,10,10,10,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,30,30,28,28,18,18,10},
{10,18,18,28,28,28,28,28,28,18,18,10},
{10,18,18,18,18,18,18,18,18,18,18,10},
{10,10,10,10,10,10,10,10,10,10,10,10}。
3. method according to claim 1 is characterized in that, described night, the computational methods of average brightness were:
The image of current image frame is divided into grid; Average brightness is:
AePreviewAverageLuma=Luma(i，j)*weight(i，j)/(WINVC*WINHC)2.3
Wherein, (i j) is raster brightness mean value to Luma, and (i j) is the raster brightness weight to weight; WINVC is this grid grid number in the vertical direction, and WINHC is that this grid is at the grid number of vertical direction.
Weight (i, j) matrix of luminance weights be night the luminance weights matrix be:
{1,1,1,1,1,1,1,1,1,1,1,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,4,1},
{1,4,4,8,15,30,30,15,8,4,1,1},
{1,4,4,8,15,15,15,15,8,4,4,1},
{1,4,4,4,4,4,4,4,4,4,4,1},
{1,1,1,1,1,1,1,1,1,1,1,1}。
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Cited By (5)
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| CN104301619A (en) * | 2014-02-24 | 2015-01-21 | 凯迈（洛阳）测控有限公司 | Fast camera exposure time automatic adjusting method and device |
| CN105187731A (en) * | 2015-09-18 | 2015-12-23 | 中电海康集团有限公司 | Day-night switching method and device based on forward collision warning |
| CN109889733A (en) * | 2019-03-25 | 2019-06-14 | 福州瑞芯微电子股份有限公司 | A kind of automatic exposure compensation method, storage medium and computer |
| CN109923856A (en) * | 2017-05-11 | 2019-06-21 | 深圳市大疆创新科技有限公司 | Light supplementing control device, system, method and mobile device |
| CN109936698A (en) * | 2017-12-18 | 2019-06-25 | 杭州海康威视数字技术股份有限公司 | A kind of automatic exposure control method, device, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109936698A (en) * | 2017-12-18 | 2019-06-25 | 杭州海康威视数字技术股份有限公司 | A kind of automatic exposure control method, device, electronic equipment and storage medium |
| CN109936698B (en) * | 2017-12-18 | 2021-07-02 | 杭州海康威视数字技术股份有限公司 | Automatic exposure control method and device, electronic equipment and storage medium |
| CN109889733A (en) * | 2019-03-25 | 2019-06-14 | 福州瑞芯微电子股份有限公司 | A kind of automatic exposure compensation method, storage medium and computer |
| CN109889733B (en) * | 2019-03-25 | 2021-07-02 | 瑞芯微电子股份有限公司 | Automatic exposure compensation method, storage medium and computer |
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