CN110602414A - Camera automatic exposure method based on ambient brightness and image information entropy - Google Patents
Camera automatic exposure method based on ambient brightness and image information entropy Download PDFInfo
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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
The invention provides an automatic camera exposure method based on environment brightness and image information entropy, which comprises the steps of S1, calculating the average brightness of a graph and the information entropy of the image; calculating the average brightness and the image information entropy of the image according to the brightness histogram of the graph; and S2, obtaining the brightness of the automatic exposure target by weighting calculation by using the entropy of the image information. The camera automatic exposure method based on the environmental brightness and the image information is realized in the scheme of a 3559A processor and an IMX305 image sensor, and through tests, the camera automatic exposure method effectively solves the problem of scene adaptability in the traditional AE method, can obtain better results no matter a scene with wide dynamic range, high contrast and rich details is processed, and fully meets the requirements of the current video monitoring field of the intelligent security industry.
Description
Technical Field
The invention belongs to the field of video monitoring in the intelligent security industry, and particularly relates to an automatic camera exposure method based on ambient brightness and image information entropy.
Background
For an Auto-Exposure (AE) method Of a camera, a conventional implementation is to use an average brightness manner based on an image or an average brightness manner weighted by a Region Of Interest (ROI) as a light metering reference Of the image, or a manner Of finding a maximum value according to a dynamic adjustment image information entropy as an object Of the Auto-Exposure. However, cameras in the video monitoring field of the intelligent security video industry are widely applied to indoor and outdoor scenes with various brightness, contrast and dynamic ranges, and the above modes have obvious problems in scene adaptability.
Disclosure of Invention
In view of the above, the present invention provides an automatic camera exposure method based on ambient brightness and image information entropy, which aims to overcome the above-mentioned defects in the prior art.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a camera automatic exposure method based on ambient brightness and image information entropy comprises the following steps:
s1, calculating the average brightness of the graph and the information entropy of the image; calculating the average brightness and the image information entropy of the image according to the brightness histogram of the graph;
s2, obtaining the brightness of the automatic exposure target through weighting calculation by using the entropy of the image information; calculating target brightness weighting according to the image information entropy obtained in the step S1, and obtaining weighted automatic exposure target brightness together with the input peripheral brightness through calculation;
s3, calculating the current environment equivalent brightness; according to the input current exposure time and the gain value, obtaining an environment brightness factor, and calculating the final brightness value of the current image;
s4, calculating the automatic exposure adjustment quantity: according to the weighted automatic exposure target brightness and the final image brightness value, the size and the direction of an exposure value which should be adjusted in the current frame are calculated;
s5, distributing the gain of the automatic exposure time; the adjustment amount of the exposure time and the gain is allocated based on the magnitude and direction of the exposure value obtained in S4.
Further, the specific method of step S1 includes:
s11, creating image brightness histogram hist based on the exposure value of the camera frame information, and obtaining ith order histogram hist(i)Probability P of(i)Comprises the following steps:
p(i)＝hist(i)/(h*w)
wherein i is the gray scale number of the image brightness histogram hist, in the 8-bit digital image system, the value range of i is 0 to 255, and h and w are the height and width of the image respectively;
s12, obtaining the information entropy H of the frame image according to an information entropy calculation formula:
s13, average brightness L of image is obtainedavgComprises the following steps:
further, the specific method of step S2 includes: system target brightness L according to external inputinImage information entropy threshold HthTo obtain the brightness L of the image automatic exposure targettar：
Ltar＝Lin-lunit*max(0，floor(H-Hth)/Huint)
Wherein lunitWeight compensated for target luminance, HuintThe floor is the unit of entropy calculation of image information and is rounding down.
Further, the specific method of step S3 includes:
s31, according to the exposure time S and the gain G of the current system, using the maximum exposure time S of the systemmaxAnd a maximum gain value GmaxCalculating the external environment brightness ratio f of the current framet:
ft＝S*G/(Smax*Gmax)
Since the exposure time S cannot be 0, f is known from the formulatThe value range is (0, 1)]，ftThe larger the size, the smaller the current scene luminance is justified.
S32, obtaining the external environment brightness coefficient f according to S31tCalculating the ambient brightness f in the current sceneenv:
For the scene with dark and bright ambient brightness, there are histogram brightness weight functions WdAnd WbAccording to the ambient brightness fenvIt can be according to the formula:
Wf＝Wd*fenv+Wb*(1-fenv)
calculating a fitted histogram luminance weight function WfThen, the weight mapping basis of the brightness of the current image is obtained, and according to a formula:
obtaining the final brightness value L of the current imagef。
Further, the specific method of step S4 includes: comparing the luminance L of the auto-exposure targettarAnd the image brightness LfThe exposure deviation E is obtained as a target for the next frame adjustment according to the following formula:
further, the specific method of step S5 includes: based on the exposure deviation E obtained in S4, according to the exposure adjustment formulaDynamic allocation of exposure time S, digital gain G of camera systemDAnd an analog gain GAIn accordance with the increase in exposureStage S>GA>GDPrinciple of (1), exposure reduction in accordance with priority GD>GA>The principle of S.
Compared with the prior art, the invention has the following advantages:
the camera automatic exposure method based on the environmental brightness and the image information is realized in the scheme of a 3559A processor and an IMX305 image sensor, and through tests, the camera automatic exposure method effectively solves the problem of scene adaptability in the traditional AE method, can obtain better results no matter a scene with wide dynamic range, high contrast and rich details is processed, and fully meets the requirements of the current video monitoring field of the intelligent security industry.
Compared with the traditional automatic exposure algorithm based on image brightness statistical information, the invention introduces the environment brightness information, the histogram of the image and the information entropy as the reference of the automatic exposure system, firstly, the average brightness and the information entropy of the image are solved through the brightness histogram, then, the new target brightness is calculated according to the information entropy on the basis of the original target brightness, and simultaneously, the environment brightness coefficient is obtained according to the current exposure and the gain of the camera, weighting and mapping the average brightness of the image to obtain the final brightness of the current frame, and obtaining the adjustment range and direction of the exposure gain through the automatic exposure control logic, thereby achieving the purpose of controlling the automatic exposure of the camera in real time at high speed, the invention is suitable for the application of video cameras in various scenes, on the basis of guaranteeing the real-time performance, the adaptability and the exposure effect of the camera to the scene are effectively improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the invention without limitation. In the drawings:
fig. 1 is a flowchart of the automatic exposure method of a camera based on ambient brightness and image information according to the embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "central," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings, which are merely for convenience in describing the invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and are therefore not to be construed as limiting the invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.
In the description of the invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted", "connected" and "connected" are to be construed broadly, e.g. as being fixed or detachable or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the creation of the present invention can be understood by those of ordinary skill in the art through specific situations.
The invention will be described in detail with reference to the following embodiments with reference to the attached drawings.
An automatic exposure method for a camera based on ambient brightness and image information entropy, as shown in fig. 1, includes:
s1, calculating the average brightness of the graph and the information entropy of the image; calculating the average brightness and the image information entropy of the image according to the brightness histogram of the graph;
s2, obtaining the brightness of the automatic exposure target through weighting calculation by using the entropy of the image information; calculating target brightness weighting according to the image information entropy obtained in the step S1, and obtaining weighted automatic exposure target brightness together with the input peripheral brightness through calculation;
s3, calculating the current environment equivalent brightness; according to the input current exposure time and the gain value, obtaining an environment brightness factor, and calculating the final brightness value of the current image;
s4, calculating the automatic exposure adjustment quantity: according to the weighted automatic exposure target brightness and the final image brightness value, the size and the direction of an exposure value which should be adjusted in the current frame are calculated;
s5, distributing the gain of the automatic exposure time; the adjustment amount of the exposure time and the gain is allocated based on the magnitude and direction of the exposure value obtained in S4.
Based on the continuity of the camera frame information, the information of the nth frame may be used as a basis for calculating the exposure value of the (N + 1) th frame, and the specific method of step S1 includes:
s11, creating image brightness histogram hist based on the exposure value of the camera frame information, and obtaining ith order histogram hist(i)Probability P of(i)Comprises the following steps:
p(i)＝hist(i)/(h*w)
wherein i is the gray scale number of the image brightness histogram hist, in the 8-bit digital image system, the value range of i is 0 to 255, and h and w are the height and width of the image respectively;
s12, obtaining the information entropy H of the frame image according to an information entropy calculation formula:
s13, average brightness L of image is obtainedavgComprises the following steps:
the specific method of step S2 includes: system target brightness L according to external inputinImage information entropy threshold HthTo obtain the brightness L of the image automatic exposure targettar：
Ltar＝Lin-lunit*max(0，floor(H-Hth)/Huint)
Wherein lunitFor the weight of the target luminance compensation, l is generally takenunit＝2，HuintFor the entropy calculation unit of image information, take H hereuintAt 5000 f, floor is rounded down.
The specific method of step S3 includes:
s31, according to the exposure time S and the gain G of the current system, using the maximum exposure time S of the systemmaxAnd a maximum gain value GmaxCalculating the external environment brightness ratio f of the current framet:
ft＝S*G/(Smax*Gmax)
Since the exposure time S cannot be 0, f is known from the formulatThe value range is (0, 1)]，ftThe larger the size, the smaller the current scene luminance is justified.
S32, obtaining the external environment brightness coefficient f according to S31tCalculating the ambient brightness f in the current sceneenv:
For the scene with dark and bright ambient brightness, there are histogram brightness weight functions WdAnd WbAccording to the ambient brightness fenvIt can be according to the formula:
Wf＝Wd*fenv+Wb*(1-fenv)
calculating a fitted histogram luminance weight function WfThen, the weight mapping basis of the brightness of the current image is obtained, and according to a formula:
obtaining the final brightness value L of the current imagef。
The specific method of step S4 includes: comparing the luminance L of the auto-exposure targettarAnd the image brightness LfThe exposure deviation E is obtained as a target for the next frame adjustment according to the following formula:
the specific method of step S5 includes: based on the exposure deviation E obtained in S4, according to the exposure adjustment formulaDynamic allocation of exposure time S, digital gain G of camera systemDAnd an analog gain GAIncrease of exposure according to priority S>GA>GDPrinciple of (1), exposure reduction in accordance with priority GD>GA>The principle of S.
The camera automatic exposure method based on the environmental brightness and the image information is realized in the scheme of a 3559A processor and an IMX305 image sensor, and through tests, the camera automatic exposure method effectively solves the problem of scene adaptability in the traditional AE method, can obtain better results no matter a scene with wide dynamic range, high contrast and rich details is processed, and fully meets the requirements of the current video monitoring field of the intelligent security industry.
Compared with the traditional automatic exposure algorithm based on image brightness statistical information, the invention introduces the environment brightness information, the histogram of the image and the information entropy as the reference of the automatic exposure system, firstly, the average brightness and the information entropy of the image are solved through the brightness histogram, then, the new target brightness is calculated according to the information entropy on the basis of the original target brightness, and simultaneously, the environment brightness coefficient is obtained according to the current exposure and the gain of the camera, weighting and mapping the average brightness of the image to obtain the final brightness of the current frame, and obtaining the adjustment range and direction of the exposure gain through the automatic exposure control logic, thereby achieving the purpose of controlling the automatic exposure of the camera in real time at high speed, the invention is suitable for the application of video cameras in various scenes, on the basis of guaranteeing the real-time performance, the adaptability and the exposure effect of the camera to the scene are effectively improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the invention, so that any modifications, equivalents, improvements and the like, which are within the spirit and principle of the present invention, should be included in the scope of the present invention.
Claims (6)
1. A camera automatic exposure method based on ambient brightness and image information entropy is characterized by comprising the following steps:
s1, calculating the average brightness of the graph and the information entropy of the image; calculating the average brightness and the image information entropy of the image according to the brightness histogram of the graph;
s2, obtaining the brightness of the automatic exposure target through weighting calculation by using the entropy of the image information; calculating target brightness weighting according to the image information entropy obtained in the step S1, and obtaining weighted automatic exposure target brightness together with the input peripheral brightness through calculation;
s3, calculating the current environment equivalent brightness; according to the input current exposure time and the gain value, obtaining an environment brightness factor, and calculating the final brightness value of the current image;
s4, calculating the automatic exposure adjustment quantity: according to the weighted automatic exposure target brightness and the final image brightness value, the size and the direction of an exposure value which should be adjusted in the current frame are calculated;
s5, distributing the gain of the automatic exposure time; the adjustment amount of the exposure time and the gain is allocated based on the magnitude and direction of the exposure value obtained in S4.
2. The method for camera automatic exposure based on ambient brightness and image information entropy as claimed in claim 1, wherein the specific method of step S1 includes:
s11, creating image brightness histogram hist based on the exposure value of the camera frame information, and obtaining ith order histogram hist(i)Probability P of(i)Comprises the following steps:
p(i)＝hist(i)/(h*w)
wherein i is the gray scale number of the image brightness histogram hist, in the 8-bit digital image system, the value range of i is 0 to 255, and h and w are the height and width of the image respectively;
s12, obtaining the information entropy H of the frame image according to an information entropy calculation formula:
s13, average brightness L of image is obtainedavgComprises the following steps:
。
3. the method for camera automatic exposure based on ambient brightness and image information entropy as claimed in claim 1, wherein the specific method of step S2 includes: system target brightness L according to external inputinImage information entropy threshold HthTo obtain the brightness L of the image automatic exposure targettar：
Ltar＝Lin-lunit*max(0，floor(H-Hth)/Huint)
Wherein lunitWeight compensated for target luminance, HuintThe floor is the unit of entropy calculation of image information and is rounding down.
4. The method for camera automatic exposure based on ambient brightness and image information entropy as claimed in claim 1, wherein the specific method of step S3 includes:
s31, according to the exposure time S and the gain G of the current system, using the maximum exposure time S of the systemmaxAnd a maximum gain value GmaxCalculating the external environment brightness ratio f of the current framet：
ft＝S*G/(Smax*Gmax)
Since the exposure time S cannot be 0, f is known from the formulatThe value range is (0, 1)]，ftThe larger the size, the smaller the current scene luminance is justified.
S32, obtaining the external environment brightness coefficient f according to S31tCalculating the ambient brightness f in the current sceneenv：
For the scene with dark and bright ambient brightness, there are histogram brightness weight functions WdAnd WbAccording to the ambient brightness fenvIt can be according to the formula:
Wf＝Wd*fenv+Wb*(1-fenv)
calculating a fitted histogram luminance weight function WfThen, the weight mapping basis of the brightness of the current image is obtained, and according to a formula:
obtaining the final brightness value L of the current imagef。
5. The method for camera automatic exposure based on ambient brightness and image information entropy as claimed in claim 1, wherein the specific method of step S4 includes: comparing the luminance L of the auto-exposure targettarAnd the image brightness LfThe exposure deviation E is obtained as a target for the next frame adjustment according to the following formula:
。
6. the method for camera automatic exposure based on ambient brightness and image information entropy as claimed in claim 5, wherein the specific method of step S5 includes: based on the exposure deviation E obtained in S4, according to the exposure adjustment formulaDynamic allocation of exposure time S, digital gain G of camera systemDAnd an analog gain GAIncrease in exposure according to priority S > GA＞GDPrinciple of (1), exposure reduction in accordance with priority GD＞GAThe principle of > S.
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