CN107197167B - Method and device for obtaining image - Google Patents
Method and device for obtaining image Download PDFInfo
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- CN107197167B CN107197167B CN201610144334.5A CN201610144334A CN107197167B CN 107197167 B CN107197167 B CN 107197167B CN 201610144334 A CN201610144334 A CN 201610144334A CN 107197167 B CN107197167 B CN 107197167B
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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
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
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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
- H04N23/741—Circuitry for compensating brightness variation in the scene by increasing the dynamic range of the image compared to the dynamic range of the electronic image sensors
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/70—SSIS architectures; Circuits associated therewith
- H04N25/71—Charge-coupled device [CCD] sensors; Charge-transfer registers specially adapted for CCD sensors
Abstract
The embodiment of the invention provides a method and a device for obtaining an image, wherein the method comprises the following steps: monitoring whether an image acquisition signal is received; if yes, obtaining a first image for acquiring the long frame image BThe exposure and a second exposure used for acquiring the short frame image B'; collecting a long frame image B and a short frame image B' according to the first exposure and the second exposure; generating a synthetic image from the long frame image B and the short frame image B' according to a preset image synthesis rule; the first exposure amount and the second exposure amount are calculated by: obtaining the exposure ratio k of the last acquired image; obtaining the gray scale statistic value G of the last acquired long frame image AA(ii) a According to the gray scale statistic value GADetermining a first exposure amount; the second exposure amount is calculated from the exposure ratio k and the first exposure amount. By applying the scheme provided by the embodiment of the invention, the exposure ratio can be dynamically adjusted, and different exposure ratios are used for scenes with different dynamic ranges, so that a high-quality image is obtained.
Description
Technical Field
The invention relates to the technical field of image acquisition, in particular to a method and a device for acquiring an image.
Background
In some shooting scenes with excessive contrast, a general camera is limited by the photosensitive characteristics of a sensing Device, such as a CCD (Charge-coupled Device), and the image output by the camera often appears in a bright area or a dark area, where the bright area becomes white due to overexposure and the dark area becomes black due to underexposure, which seriously affects the image quality. In general, the ratio of the maximum luminance to the minimum luminance in an image is referred to as a dynamic range. In general, the higher the dynamic range, the larger the ratio of the maximum luminance to the minimum luminance in the captured image is, the more the image quality is affected by the light-sensing characteristics. In view of the situation, the wide dynamic technology is developed, and the problem is well solved.
At present, most of image exposures based on the wide dynamic technology adopt a mean value exposure mode. However, in some high dynamic range scenes, the bright area occupies a larger image area, and the dark area occupies a smaller image area, and if the mean exposure mode is adopted for image acquisition, the image brightness of the dark scene is easily lowered, so that the image detail expression of the partial area is poor, and the quality of the obtained image is poor.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for obtaining an image, so as to obtain a high-quality image under image acquisition scenes with different dynamic ranges.
In order to achieve the above object, the embodiment of the present invention discloses a method for obtaining an image, which is applied to an image acquisition device, wherein the image acquisition device acquires two images, namely a long frame image and a short frame image, after receiving an image acquisition signal each time; wherein the exposure time of the long frame image is longer than the exposure time of the short frame image, the method comprising:
monitoring whether an image acquisition signal is received;
if yes, obtaining a first exposure used for acquiring the long frame image B and a second exposure used for acquiring the short frame image B';
acquiring the long frame image B and the short frame image B' according to the first exposure and the second exposure;
generating a composite image from the long frame image B and the short frame image B' according to a preset image synthesis rule;
wherein the first exposure amount and the second exposure amount are calculated by:
obtaining the exposure ratio k of the last acquired image; the exposure ratio is the ratio of the exposure of the acquired long frame image to the exposure of the acquired short frame image under the same image acquisition signal;
obtaining the gray scale statistic value G of the last acquired long frame image AA；
According to the gray scale statistic value GADetermining the first exposure amount;
and calculating the second exposure according to the exposure ratio k and the first exposure.
Preferably, the gray scale statistic value G of the last acquired long frame image A is obtainedAThe method comprises the following steps:
according to a preset weighted value calculation rule, calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time;
obtaining the gray scale statistic value G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting the number of pixels with gray scale value i, Q, in the long frame image AiA weight value of the gray value i is represented.
Preferably, the calculating the weight value of each gray value in the gray scale range corresponding to the long frame image a collected last time according to the preset weight value calculation rule includes:
calculating the probability distribution value of each gray value in the gray range corresponding to the long frame image A according to the gray value of the pixel point in the long frame image A collected last time;
scaling the probability distribution value of each gray value according to the preset probability scaling coefficient of each gray value; wherein the probability scaling factor is used for controlling the degree of preferential exposure of dark areas in the image;
calculating the cumulative probability value of the probability distribution value of each gray value in the long frame image A according to the sequence of the gray values from large to small;
calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset probability scaling factor of the gray value i.
Preferably, the exposure dose includes: an exposure time component and a gain component;
the calculating the second exposure amount according to the exposure ratio k and the first exposure amount comprises:
the second exposure amount is calculated according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure amount, GainBA gain component of the first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure amount, GainB′Is a gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
Preferably, before the calculating the second exposure amount according to the exposure ratio k and the first exposure amount, the method further includes:
the long frame image A and the short frame image A' are combined to form an image CAA′From the composite image CAA′Calculating a dynamic range factor F aiming at an exposure ratio according to the gray value of the middle pixel point; wherein the dynamic range factor F is used to adjust the exposure ratio k;
adjusting the dynamic range factor F according to the value range of a preset dynamic range factor;
and adjusting the exposure ratio k according to the adjusted state range factor F.
Preferably, the image C is synthesizedAA′Grey value of middle pixel point, meterCalculating a dynamic range factor F for the exposure ratio, comprising:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting a gray level median value in a gray level range (a, b) in a Bayer domain; the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
In order to achieve the above object, the embodiment of the present invention discloses an apparatus for obtaining an image, which is applied to an image acquisition device, wherein the image acquisition device acquires two images, namely a long frame image and a short frame image, after receiving an image acquisition signal each time; wherein the exposure time of the long frame image is longer than the exposure time of the short frame image, the apparatus comprising:
the acquisition signal monitoring module is used for monitoring whether an image acquisition signal is received or not;
the exposure obtaining module is used for obtaining a first exposure for collecting the long frame image B and a second exposure for collecting the short frame image B' when the image collecting signal is monitored to be received;
the image acquisition module is used for acquiring the long frame image B and the short frame image B' according to the first exposure and the second exposure;
the image synthesis module is used for generating a synthetic image from the long frame image B and the short frame image B' according to a preset image synthesis rule;
wherein the apparatus further comprises an exposure calculation module comprising:
the exposure ratio obtaining submodule is used for obtaining an exposure ratio k of the last acquired image; the exposure ratio is the ratio of the exposure of the acquired long frame image to the exposure of the acquired short frame image under the same image acquisition signal;
a gray scale statistic submodule for obtaining gray scale statistic value G of the last collected long frame image AA；
A first exposure determining submodule for determining the first exposure according to the gray scale statistic value GADetermining the first exposure amount;
and the second exposure calculation submodule is used for calculating the second exposure according to the exposure ratio k and the first exposure.
Preferably, the grayscale statistics sub-module includes:
the weighted value calculating unit is used for calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time according to a preset weighted value calculating rule;
a gray scale statistic unit for obtaining the gray scale statistic value G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting the number of pixels with gray scale value i, Q, in the long frame image AiA weight value of the gray value i is represented.
Preferably, the weighted value calculating unit is specifically configured to:
calculating the probability distribution value of each gray value in the gray range corresponding to the long frame image A according to the gray value of the pixel point in the long frame image A collected last time;
scaling the probability distribution value of each gray value according to the preset probability scaling coefficient of each gray value; wherein the probability scaling factor is used for controlling the degree of preferential exposure of dark areas in the image;
calculating the cumulative probability value of the probability distribution value of each gray value in the long frame image A according to the sequence of the gray values from large to small;
calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset probability scaling factor of the gray value i.
Preferably, the exposure dose includes: an exposure time component and a gain component;
the second exposure calculation submodule is specifically configured to:
the second exposure amount is calculated according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure amount, GainBA gain component of the first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure amount, GainB′Is a gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
Preferably, the exposure calculation module further includes:
a dynamic range factor calculation submodule for calculating the second exposure amount by the second exposure amount calculation submodule according to the exposure ratio k and the first exposure amount, and before the long-frame image is subjected to calculation of the second exposure amount by the second exposure amount calculation submoduleA and the short frame image A' to form a composite image CAA′From the composite image CAA′Calculating a dynamic range factor F aiming at an exposure ratio according to the gray value of the middle pixel point; wherein the dynamic range factor F is used to adjust the exposure ratio k;
the dynamic range factor adjusting submodule is used for adjusting the dynamic range factor F according to the value range of a preset dynamic range factor;
and the exposure ratio adjusting submodule is used for adjusting the exposure ratio k according to the adjusted state range factor F.
Preferably, the dynamic range factor calculating sub-module is specifically configured to:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting a gray level median value in a gray level range (a, b) in a Bayer domain; the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
The method and the device for acquiring the image are applied to image acquisition equipment, the image acquisition equipment monitors whether an image acquisition signal is received or not, when the signal is detected, a first exposure used for acquiring a long frame image B and a second exposure used for acquiring a short frame image B 'are acquired, and the long frame image B and the short frame image B' are acquired according to the first exposure and the second exposure; then, the long frame image B and the short frame image B' are generated into a composite image according to a preset image composition rule. Wherein the first exposure amount and the second exposure amount are set as followsAnd calculating to obtain: obtaining the exposure ratio k of the last acquired image; obtaining the gray scale statistic value G of the last acquired long frame image AA(ii) a According to the gray scale statistic value GADetermining a first exposure amount; the second exposure amount is calculated based on the exposure ratio k and the first exposure amount.
According to the technical scheme, the exposure ratio can be dynamically adjusted by applying the scheme provided by the embodiment of the invention, and different exposure ratios are used for scenes with different dynamic ranges, so that a high-quality image is obtained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1a is a schematic flow chart illustrating a method for obtaining an image according to an embodiment of the present invention;
FIG. 1b is a gray level histogram curve of a long frame image A according to an embodiment of the present invention;
fig. 1c is a histogram curve for representing the probability distribution value of each gray value in the gray range corresponding to the long frame image a according to the embodiment of the present invention;
FIG. 1d is a histogram curve of probability scaling factors for gray scale values according to an embodiment of the present invention;
fig. 1e is a histogram curve obtained by scaling the probability distribution value of each gray value in the gray scale range corresponding to the long frame image a according to fig. 1d according to the embodiment of the present invention;
FIG. 1f is a histogram plot of cumulative probability distribution values for representing probability distribution values of various gray values in a long frame image A according to an embodiment of the present invention;
fig. 1g is a histogram curve of weighted values for representing any gray value i in a gray range corresponding to the long frame image a according to the embodiment of the present invention;
FIG. 1h is a distribution histogram curve of gray values of a composite image in a Bayer domain in a scene with different dynamic ranges according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an apparatus for obtaining an image according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1a, which is a schematic flowchart of a method for obtaining an image according to an embodiment of the present invention, the method is applied to an image capturing device, and the image capturing device captures two images, namely a long frame image and a short frame image, each time after receiving an image capturing signal; wherein the exposure time of the long frame image is longer than that of the short frame image.
It should be noted that the exposure time of the two acquired images is different, and the exposure time of the long frame image is longer than that of the short frame image. Generally, the longer the exposure time is, the more light rays are received by a photosensitive chip in the image acquisition equipment, and the acquired image is easy to be brighter; conversely, the shorter the exposure time, the less light the photosensitive chip in the image capture device receives, and the more dark the captured image is.
The "image acquisition device" mentioned here may be an image acquisition device composed of two ordinary cameras, where an ordinary camera refers to an image acquisition device that acquires only one image after receiving an image acquisition signal, and one of the two ordinary cameras is used for acquiring a long frame image and the other is used for acquiring a short frame image; the system can also be an image acquisition device consisting of a special photosensitive chip, and the special photosensitive chip can perform exposure twice and acquire two images after receiving an image acquisition signal. Of course, the embodiment of the present invention does not need to limit the specific form of the image capturing device, and any possible implementation manner may be applied to the present invention.
In addition, no matter what implementation form the image capturing device is implemented, the time interval between the long frame image and the short frame image captured by the image capturing device cannot be greater than the preset capture interval threshold, and if the time interval is greater than the preset capture interval threshold, for a dynamic scene, there is a possibility that a large difference occurs between images captured by the long frame image and the short frame image, which may cause the quality of a synthesized image to be degraded.
Specifically, the method for obtaining the image includes the following steps:
step S101: whether an image acquisition signal is received or not is monitored, and if so, the step S102 is executed.
The image capturing signal refers to a signal for triggering the image capturing device to capture an image, and specifically, may be a signal for controlling a photosensitive chip in the image capturing device to perform image exposure.
Step S102: a first exposure amount for acquiring the long frame image B and a second exposure amount for acquiring the short frame image B' are obtained.
Wherein the first exposure amount and the second exposure amount are calculated in the following way:
(11) the exposure ratio k of the last acquired image is obtained.
The exposure ratio is the ratio of the exposure of the long frame image to the exposure of the short frame image under the same image acquisition signal.
(12) Obtaining the gray scale statistic value G of the last acquired long frame image AA。
The first embodiment is as follows: the gray scale statistic value G of the last acquired long frame image A can be obtained according to the following stepsA：
And (12.1) according to a preset weighted value calculation rule, calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time.
It should be noted that the "preset weighted value calculation rule" mentioned herein is a weighted value calculation rule obtained according to the gray value of the image, and the present invention does not need to limit the specific implementation form of the preset weighted value calculation rule, and those skilled in the art need to reasonably set the rule according to the specific situation in the practical application.
(12.2) obtaining the gray scale statistic G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting the number of pixels with a gray value i, Q, in the long-frame image AiA weight value of the gray value i is represented.
It should be noted that, in the first embodiment, only the gray scale statistic G of the long frame image a acquired last time is obtainedAThe present invention is not limited to the above specific implementation form, and any possible implementation form can be applied to the present invention.
Next, referring to fig. 1b to fig. 1g, a specific process of the step (12.1) of calculating a weighted value of each gray value in the gray range corresponding to the long-frame image a collected last time is described, and referring to fig. 1b, a gray histogram curve of the long-frame image a according to the embodiment of the present invention is provided:
a. according to the gray value of the pixel point in the long frame image a collected last time, the probability distribution value of each gray value in the gray range corresponding to the long frame image a is calculated, and referring to fig. 1c, a histogram curve for representing the probability distribution value of each gray value in the gray range corresponding to the long frame image a is provided in the embodiment of the present invention. Comparing FIG. 1c with FIG. 1b, it can be seen that the curves in FIG. 1c are similar to those in FIG. 1 b.
It should be noted that, the method for obtaining the gray value of the pixel point in the long frame image a in step a belongs to the prior art, and step a counts the gray value of the pixel point in the long frame image a to obtain the probability distribution value belonging to each gray value. For example, for an 8-bit image with an image size of 30 x 30, it isThe corresponding gray scale range (i.e., gray scale) is {0, 2 }8-1) }, i.e. (0,255), there are 900 pixel points; if the number of the pixels with the gray value of 20 is 450, and the number of the pixels with the gray value of 200 is 450, then according to the method in step a, the probability distribution value with the gray value of 20 is: 450/900 is 0.5, and the probability distribution value for a gray scale value of 200 is 450/900 is 0.5. Of course, this is merely to illustrate how to calculate the probability distribution value of each gray value in the gray range corresponding to the long frame image a according to the gray values of the pixel points in the long frame image a, and the embodiment of the present invention does not need to limit the gray range of the long frame image, for example, for a 16-bit image, the image gray range may also be (0,65535).
b. Scaling the probability distribution value of each gray value according to the preset probability scaling factor of each gray value, see fig. 1d, which is a curve of the probability scaling factor for the gray value according to the embodiment of the present invention.
Wherein the probability scaling factor is used to control the degree of preferential exposure of dark areas in the image.
Further, referring to fig. 1e, a histogram curve obtained by scaling the probability distribution value of each gray value in the gray scale range corresponding to the long frame image a according to fig. 1d is provided for the embodiment of the present invention.
c. The cumulative probability values of the probability distribution values of the gray values in the long frame image a are calculated according to the sequence of the gray values from large to small, and referring to fig. 1f, the histogram curve for the cumulative probability distribution values of the gray values in the long frame image a is provided in the embodiment of the present invention.
Generally, for an 8-bit image, the gray scale range is (0,255), the pixel point with the gray scale value of 0 is a pure black pixel point, and the pixel point with the gray scale value of 255 is a pure white pixel point, so the cumulative probability value of the probability distribution value of each gray scale value in the long-frame image a is calculated according to the sequence of the gray scale values from large to small in step b, and actually, the cumulative probability value is calculated according to the sequence of the pixel points from light to dark.
As can be seen from fig. 1f, the histogram of the accumulated probability distribution values shows a decreasing trend as the gray-scale value increases, and therefore, the smaller the gray-scale value, the larger the corresponding histogram of the probability distribution values. It should be noted that the purpose of performing probability accumulation in this way is to preferentially expose a darker area in a scene so that a captured image can achieve appropriate brightness.
d. Calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset probability scaling factor of the gray value i.
Referring to fig. 1g, a histogram curve for representing a weighted value of any gray value i in a gray range corresponding to the long frame image a is provided according to an embodiment of the present invention.
It should be noted that the above steps a to d are only one exposure method for preferentially exposing the darker area in the scene, and other implementation methods are certainly possible, and the present invention is not limited thereto, and any possible implementation method can be applied to the present invention.
(13) According to the gray scale statistic value GAAnd determining the first exposure amount.
The gray scale statistic value GAThe first exposure amount may be determined according to a preset first exposure amount determination rule, or may be determined empirically by those skilled in the art. For example, assume a gray scale statistic value GAA gray scale statistic threshold value T can be preset for the gray scale statistic value of 60G(e.g., 50), clear grayscale statistic GAHas exceeded the threshold value T of the gray scale statisticGAccordingly, one skilled in the art may adjust the first exposure amount to be lower (e.g., lower) based on empirical valuesExposure time or reduced gain, etc.). In addition, please refer to steps (15) to (17) for an implementation of the first exposure amount determined according to the preset first exposure amount determination rule. Therefore, by applying the scheme provided by the embodiment of the invention, when the image acquisition device is used for image acquisition, the first exposure can be obtained according to the last acquired long frame image, and the first exposure is related to the brightness of the last acquired long frame image.
Of course, the first exposure amount is a statistical value G that can be calculated from the gray scale by way of example onlyAAdjusted, however, the embodiments of the present invention do not require how to rely on the gray scale statistic G specificallyAThe adjustment is performed and the magnitude of the adjustment is limited, and those skilled in the art need to set the adjustment according to the specific situation in the practical application.
(14) The second exposure amount is calculated based on the exposure ratio k and the first exposure amount.
Wherein the exposure amount may include: an exposure time component and a gain component.
In one implementation, the second exposure amount may be calculated according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure, GainBA gain component that is a first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure, GainB′Is the gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
It should be noted that the above-listed implementation manners for calculating the second exposure amount are only examples, and the embodiment of the present invention does not need to limit the specific form for calculating the second exposure amount, and any possible implementation manners may be applied to the present invention.
Example two:
on the basis of the first embodiment, before the step (14), the second embodiment may further include:
(15) long frame image A and short frame image A' composite image CAA′From the composite image CAA′And calculating a dynamic range factor F aiming at the exposure ratio according to the gray value of the middle pixel point.
Wherein the dynamic range factor F is used to adjust the exposure ratio k.
For example, feedback adjustment may be adopted, and when the dynamic range factor F is greater than the maximum value of the preset value range of the dynamic range factor, the exposure ratio is increased, and the dynamic range factor F may be decreased until the value falls within the value range; similarly, when the dynamic range factor F is smaller than the minimum value of the value range, the exposure ratio is reduced, and the dynamic range factor F can fall within the value range. By controlling the dynamic range factor F, control and adjustment of the exposure ratio can be achieved, so that a suitable exposure ratio can be obtained.
It should be noted that the above is only one specific way to adjust the exposure ratio k by the dynamic range factor F, but other possible implementations are also possible, and any possible implementation can be applied in the present invention.
In one implementation, the dynamic range factor F for the exposure ratio may be calculated according to the following formula:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting a gray level median value in a gray level range (a, b) in a Bayer domain; the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
A specific implementation of the above mentioned calculation of the dynamic range factor F for the exposure ratio is described below with reference to fig. 1h, where fig. 1h is drawn by a person skilled in the art from empirical data. Fig. 1h is a distribution histogram curve of gray values of a synthesized image in a Bayer domain in a scene with different dynamic ranges, where a horizontal axis represents a gray value of a pixel in the Bayer domain, and a vertical axis represents a statistical result of the number of pixels with the same gray value in the synthesized image.
As can be seen from fig. 1h, the histogram plot in fig. 1h shows such a trend regardless of the image acquired in the dynamic range scene: in the range of the region with a small gradation value (i.e., the range from the minimum value of the gradation range to the middle value of the gradation range, referred to as the first region range) and the range of the region with a large gradation value (i.e., the range from the middle value of the gradation range to the maximum value of the gradation range, referred to as the second region range), there is a peak region (simply referred to as a peak region), for example, the gradation range (0,10) in fig. 1h is the range where the peak region in the first region range is located, and the gradation range (45,60) in fig. 1h is the range where the peak region in the second region range is located.
(16) And adjusting the dynamic range factor F according to the value range of the preset dynamic range factor.
(17) And adjusting the exposure ratio k according to the adjusted state range factor F.
The steps (15) to (17) are a specific implementation of the first exposure amount determined according to the preset first exposure amount determination rule, and of course, other feasible implementations are also possible, and the present invention need not be listed here, and those skilled in the art need to make reasonable settings according to the specific situation in practical application.
Step S103: the long frame image B and the short frame image B' are acquired based on the first exposure amount and the second exposure amount.
It should be noted that, in step S103, it is necessary to acquire the long frame image B according to the first exposure amount obtained in step S102 and acquire the short frame image B' according to the second exposure amount obtained, wherein a specific image acquisition process is the prior art and is not described herein again.
Step S104: and generating a composite image by the long frame image B and the short frame image B' according to a preset image composite rule.
In one implementation, the dark region in the long frame image and the bright region in the short frame image may be synthesized to obtain a synthesized image corresponding to the long frame image B and the short frame image B'. It should be noted that, this is merely an illustration of how to generate a composite image from the long frame image B and the short frame image B' according to a preset image composition rule, and other feasible implementation manners are certainly possible, and embodiments of the present invention need not be listed here.
By applying the technical scheme provided by the embodiment of the invention, the exposure ratio can be dynamically adjusted in the process of obtaining the image by utilizing the image acquisition equipment, and different exposure ratios are used aiming at scenes with different dynamic ranges, so that a high-quality image is obtained.
As shown in fig. 2, a schematic structural diagram of an apparatus for obtaining an image according to an embodiment of the present invention is applied to an image capturing device, where the image capturing device captures two images, namely a long frame image and a short frame image, after receiving an image capturing signal each time; wherein the exposure time of the long frame image is longer than that of the short frame image.
Specifically, the apparatus for obtaining an image may include the following modules:
an acquired signal monitoring module 201, configured to monitor whether an image acquisition signal is received;
an exposure obtaining module 202, configured to, when monitoring that an image capture signal is received, obtain a first exposure for capturing a long frame image B and a second exposure for capturing a short frame image B';
the image acquisition module 203 is used for acquiring a long frame image B and a short frame image B' according to the first exposure and the second exposure;
the image synthesis module 204 is configured to generate a synthesis image from the long frame image B and the short frame image B' according to a preset image synthesis rule;
wherein, the apparatus may further comprise an exposure calculation module 205, the exposure calculation module 205 comprising: the exposure ratio acquisition sub-module, the gray scale statistics sub-module, the first exposure determination sub-module and the second exposure calculation sub-module.
Specifically, the exposure ratio obtaining submodule is configured to obtain an exposure ratio k of a last acquired image.
The exposure ratio is the ratio of the exposure of the long frame image to the exposure of the short frame image under the same image acquisition signal.
Specifically, the gray scale statistic submodule is used for obtaining a gray scale statistic value G of the long frame image A acquired last timeA。
Specifically, a first exposure amount determination sub-module for determining a first exposure amount based on the gray scale statistic value GAAnd determining the first exposure amount.
Specifically, the second exposure amount calculation submodule is configured to calculate the second exposure amount according to the exposure ratio k and the first exposure amount.
Specifically, the grayscale statistics sub-module may include:
the weighted value calculating unit is used for calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time according to a preset weighted value calculating rule;
a gray scale statistic unit for obtaining the gray scale statistic value G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting long frame imagesNumber of pixels with gray value i, QiA weight value of the gray value i is represented.
Wherein, the weighted value calculating unit is specifically configured to:
calculating the probability distribution value of each gray value in the gray range corresponding to the long frame image A according to the gray value of the pixel point in the long frame image A collected last time;
calculating the cumulative probability value of the probability distribution value of each gray value in the long-frame image A according to the sequence of the gray values from large to small;
zooming the accumulated probability value of each gray value according to the preset accumulated probability zooming coefficient of each gray value; wherein the cumulative probability scaling factor is used for controlling the degree of preferential exposure of dark areas in the image;
calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset cumulative probability scaling factor for the gray value i.
Specifically, the exposure amount may include: an exposure time component and a gain component;
the second exposure amount calculating submodule is specifically configured to calculate the second exposure amount according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure, GainBA gain component that is a first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure, GainB′Is the gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
Specifically, the exposure calculation module 205 may further include:
a dynamic range factor calculation sub-module for combining the long frame image A and the short frame image A' into an image C before the second exposure amount calculation sub-module calculates the second exposure amount based on the exposure ratio k and the first exposure amountAA′From the composite image CAA′Calculating a dynamic range factor F aiming at an exposure ratio according to the gray value of the middle pixel point; wherein, the dynamic range factor F is used for adjusting the exposure ratio k;
the dynamic range factor adjusting submodule is used for adjusting a dynamic range factor F according to the value range of a preset dynamic range factor;
and the exposure ratio adjusting submodule is used for adjusting the exposure ratio k according to the adjusted state range factor F.
Specifically, the dynamic range factor calculation submodule is specifically configured to:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting a gray level median value in a gray level range (a, b) in a Bayer domain; the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
By applying the technical scheme provided by the embodiment of the invention, the exposure ratio can be dynamically adjusted in the process of obtaining the image by utilizing the image acquisition equipment, and different exposure ratios are used aiming at scenes with different dynamic ranges, so that a high-quality image is obtained.
For the apparatus embodiment, since it is substantially similar to the method embodiment, it is described relatively simply, and reference may be made to some descriptions of the method embodiment for relevant points.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Those skilled in the art will appreciate that all or part of the steps in the above method embodiments may be implemented by a program to instruct relevant hardware to perform the steps, and the program may be stored in a computer-readable storage medium, referred to herein as a storage medium, such as: ROM/RAM, magnetic disk, optical disk, etc.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (12)
1. A method for obtaining images is applied to image acquisition equipment, and the image acquisition equipment acquires two images, namely a long frame image and a short frame image after receiving an image acquisition signal each time; wherein the exposure time of the long frame image is longer than the exposure time of the short frame image, the method comprising:
monitoring whether an image acquisition signal is received;
if yes, obtaining a first exposure used for acquiring the long frame image B and a second exposure used for acquiring the short frame image B';
acquiring the long frame image B and the short frame image B' according to the first exposure and the second exposure;
generating a composite image from the long frame image B and the short frame image B' according to a preset image synthesis rule;
wherein the first exposure amount and the second exposure amount are calculated by:
obtaining the exposure ratio k of the last acquired image; the exposure ratio is the ratio of the exposure of the acquired long frame image to the exposure of the acquired short frame image under the same image acquisition signal;
obtaining the gray scale statistic value G of the last acquired long frame image AA；
According to the gray scale statistic value GADetermining the first exposure amount;
and calculating the second exposure according to the exposure ratio k and the first exposure.
2. The method of claim 1, wherein obtaining the gray scale statistic G of the last acquired long frame image AAThe method comprises the following steps:
according to a preset weighted value calculation rule, calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time;
obtaining the gray scale statistic value G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting the number of pixels with gray scale value i, Q, in the long frame image AiA weight value of the gray value i is represented.
3. The method according to claim 2, wherein the calculating the weighted value of each gray value in the gray range corresponding to the last acquired long frame image a according to the preset weighted value calculation rule comprises:
calculating the probability distribution value of each gray value in the gray range corresponding to the long frame image A according to the gray value of the pixel point in the long frame image A collected last time;
scaling the probability distribution value of each gray value according to the preset probability scaling coefficient of each gray value; wherein the probability scaling factor is used for controlling the degree of preferential exposure of dark areas in the image;
calculating the cumulative probability value of the probability distribution value of each gray value in the long frame image A according to the sequence of the gray values from large to small;
calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset probability scaling factor of the gray value i.
4. The method of any of claims 1-3, wherein said calculating the second exposure amount from the exposure ratio k and the first exposure amount comprises:
the second exposure amount is calculated according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure amount, GainBA gain component of the first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure amount, GainB′Is a gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
5. The method according to any one of claims 1-3, wherein before said calculating said second exposure amount according to said exposure ratio k and said first exposure amount, further comprising:
the long frame image A and the short frame image A' are combined to form an image CAA′From the composite image CAA′Calculating a dynamic range factor F aiming at an exposure ratio according to the gray value of the middle pixel point; the dynamic range factor F is used for adjusting the exposure ratio k, and the short frame image A' is a short frame image acquired last time;
adjusting the dynamic range factor F according to the value range of a preset dynamic range factor;
and adjusting the exposure ratio k according to the adjusted dynamic range factor F.
6. The method of claim 5, wherein the image C is a composite image ofAA′Calculating a dynamic range factor F aiming at an exposure ratio by the gray value of the middle pixel point, wherein the calculation comprises the following steps:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting ash in Bayer domainMedian gray level values within the range of degrees (a, b); the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
7. A device for obtaining images is applied to image acquisition equipment, and the image acquisition equipment acquires two images, namely a long frame image and a short frame image after receiving an image acquisition signal every time; wherein the exposure time of the long frame image is longer than the exposure time of the short frame image, the apparatus comprising:
the acquisition signal monitoring module is used for monitoring whether an image acquisition signal is received or not;
the exposure obtaining module is used for obtaining a first exposure for collecting the long frame image B and a second exposure for collecting the short frame image B' when the image collecting signal is monitored to be received;
the image acquisition module is used for acquiring the long frame image B and the short frame image B' according to the first exposure and the second exposure;
the image synthesis module is used for generating a synthetic image from the long frame image B and the short frame image B' according to a preset image synthesis rule;
wherein the apparatus further comprises an exposure calculation module comprising:
the exposure ratio obtaining submodule is used for obtaining an exposure ratio k of the last acquired image; the exposure ratio is the ratio of the exposure of the acquired long frame image to the exposure of the acquired short frame image under the same image acquisition signal;
a gray scale statistics sub-module which is connected with the gray scale statistics sub-module,obtaining gray scale statistic value G of last collected long frame image AA；
A first exposure determining submodule for determining the first exposure according to the gray scale statistic value GADetermining the first exposure amount;
and the second exposure calculation submodule is used for calculating the second exposure according to the exposure ratio k and the first exposure.
8. The apparatus of claim 7, wherein the gray scale statistics submodule comprises:
the weighted value calculating unit is used for calculating the weighted value of each gray value in the gray range corresponding to the long frame image A acquired last time according to a preset weighted value calculating rule;
a gray scale statistic unit for obtaining the gray scale statistic value G of the long frame image A according to the following formulaA：
Wherein i represents any gray value in the gray range corresponding to the long frame image A, and HiRepresenting the number of pixels with gray scale value i, Q, in the long frame image AiA weight value of the gray value i is represented.
9. The apparatus of claim 8, wherein the weighting value calculating unit is specifically configured to:
calculating the probability distribution value of each gray value in the gray range corresponding to the long frame image A according to the gray value of the pixel point in the long frame image A collected last time;
scaling the probability distribution value of each gray value according to the preset probability scaling coefficient of each gray value; wherein the probability scaling factor is used for controlling the degree of preferential exposure of dark areas in the image;
calculating the cumulative probability value of the probability distribution value of each gray value in the long frame image A according to the sequence of the gray values from large to small;
calculating the weighted value of each gray value in the gray range corresponding to the long frame image A according to the following expression:
Qi＝Pi′-tiPi；
wherein Q isiWeight value P representing any gray value i in the gray range corresponding to the long frame image AiIs a probability distribution value, P, of a gray value ii' cumulative probability value of gray value i, tiIs a preset probability scaling factor of the gray value i.
10. The apparatus according to any of claims 7-9, wherein the second exposure calculation submodule is specifically configured to:
the second exposure amount is calculated according to the following expression:
AEB′＝min(TMAXB′,SAEB′)，
wherein AE isBIs the exposure time component of the first exposure amount, GainBA gain component of the first exposure amount; SAEB′For the second exposure amount, AEB′Is the exposure time component of the second exposure amount, GainB′Is a gain component of the second exposure, TMAXB′The exposure time is the preset maximum short frame image exposure time.
11. The apparatus of any of claims 7-9, wherein the exposure calculation module further comprises:
a dynamic range factor calculation submodule for calculating the second exposure according to the exposure ratio k and the first exposure in the second exposure calculation submoduleA light quantity, before the second exposure is calculated, the long frame image A and the short frame image A' are combined to form an image CAA′From the composite image CAA′Calculating a dynamic range factor F aiming at an exposure ratio according to the gray value of the middle pixel point; the dynamic range factor F is used for adjusting the exposure ratio k, and the short frame image A' is a short frame image acquired last time;
the dynamic range factor adjusting submodule is used for adjusting the dynamic range factor F according to the value range of a preset dynamic range factor;
and the exposure ratio adjusting submodule is used for adjusting the exposure ratio k according to the adjusted dynamic range factor F.
12. The apparatus according to claim 11, wherein the dynamic range factor calculation submodule is specifically configured to:
obtaining the composite image CAA′Presetting peak region intervals (c, d) in a sub-gray scale range (m, b) in a Bayer domain; wherein m is the composite image CAA′Presetting a gray level median value in a gray level range (a, b) in a Bayer domain; the preset gray scale range is defined by the composite image CAA′Determining the gray scale of the image; c. d are each an integer and c<d；
The dynamic range factor F for the exposure ratio is calculated according to the following formula:
wherein n is a gray value corresponding to a peak value in a peak region within the preset sub-gray range (m, b); hiThe gray value is a gray value statistic value corresponding to the gray value i; a. b are each an integer and a<b。
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| CN110830727B (en) * | 2018-08-07 | 2021-06-22 | 浙江宇视科技有限公司 | Automatic exposure ratio adjusting method and device |
| CN110891146B (en) * | 2018-09-10 | 2021-12-28 | 浙江宇视科技有限公司 | Strong light inhibition method and device |
| CN111601044B (en) * | 2019-02-20 | 2022-09-16 | 杭州海康威视数字技术股份有限公司 | Image exposure time ratio determining method and device |
| CN110213499B (en) * | 2019-06-11 | 2021-08-03 | Oppo广东移动通信有限公司 | Image processing method and device, electronic equipment and computer readable storage medium |
| CN110248108B (en) * | 2019-06-14 | 2020-11-06 | 浙江大华技术股份有限公司 | Exposure adjustment and dynamic range determination method under wide dynamic state and related device |
| CN115314629B (en) * | 2021-05-08 | 2024-03-01 | 杭州海康威视数字技术股份有限公司 | Imaging method, imaging system and camera |
| CN113572972B (en) * | 2021-07-05 | 2022-04-12 | 深圳市阿达视高新技术有限公司 | High dynamic range image synthesis method, system, image processing apparatus and medium |
| CN113905194A (en) * | 2021-08-31 | 2022-01-07 | 浙江大华技术股份有限公司 | Exposure ratio processing method, terminal equipment and computer storage medium |
| CN113808222A (en) * | 2021-10-08 | 2021-12-17 | 上海肇观电子科技有限公司 | Image processing method, electronic device, and storage medium |
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