WO2020006907A1 - 一种拍摄控制方法、终端及计算机可读存储介质 - Google Patents

一种拍摄控制方法、终端及计算机可读存储介质 Download PDF

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Publication number
WO2020006907A1
WO2020006907A1 PCT/CN2018/108677 CN2018108677W WO2020006907A1 WO 2020006907 A1 WO2020006907 A1 WO 2020006907A1 CN 2018108677 W CN2018108677 W CN 2018108677W WO 2020006907 A1 WO2020006907 A1 WO 2020006907A1
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Prior art keywords
image
gray level
gray
grayscale
interval
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PCT/CN2018/108677
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English (en)
French (fr)
Inventor
曾伟
周宝
王健宗
肖京
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Ping An Technology Shenzhen Co Ltd
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Ping An Technology Shenzhen Co Ltd
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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
    • H04N23/80—Camera processing pipelines; Components thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects
    • H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/67—Focus control based on electronic image sensor signals
    • 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
    • H04N23/76—Circuitry for compensating brightness variation in the scene by influencing the image signals

Definitions

  • the present application relates to the field of computer technology, and in particular, to a shooting control method, a terminal, and a computer-readable storage medium.
  • smart terminals such as mobile terminals, smart watches, tablet computers, and robots have more and more functions.
  • one of the most basic and user-used functions is the camera function of the camera device of the smart terminal.
  • the photographic subject in the process of taking a picture by the user through the camera device of the smart terminal, often due to changes in ambient light, the photographic subject cannot be recognized normally. Therefore, how to more effectively improve the shooting effect in various environments has become a research hotspot.
  • the embodiments of the present application provide a shooting control method, a terminal, and a computer-readable storage medium, which can dynamically adjust image exposure, enhance image contrast, and improve the sharpness of a captured image.
  • an embodiment of the present application provides a shooting control method.
  • the method includes:
  • the exposure of the grayscale image is adjusted according to the cumulative probability of each grayscale interval, and image shooting is performed according to the adjusted exposure degree, where the cumulative probability is one of the distribution probability of the grayscale within the grayscale interval. with.
  • an embodiment of the present application provides a terminal, and the terminal includes a unit for executing the method in the first aspect.
  • an embodiment of the present application provides another terminal, including a processor, an input device, an output device, and a memory.
  • the processor, the input device, the output device, and the memory are connected to each other, where the memory is used for storing
  • a computer program supporting a terminal to execute the above method the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method of the first aspect.
  • an embodiment of the present application provides a computer-readable storage medium.
  • the computer storage medium stores a computer program, where the computer program includes program instructions, and the program instructions cause the processing when executed by a processor.
  • the processor performs the method of the first aspect.
  • the image exposure is adjusted according to the distribution probability of the gray levels of each pixel in the gray image and the cumulative probability of each gray level interval, thereby achieving dynamic adjustment of the image exposure, enhancing image contrast, and improving The sharpness of the captured image.
  • FIG. 1 is a schematic flowchart of a shooting control method according to an embodiment of the present application
  • FIG. 2 is a schematic flowchart of another shooting control method according to an embodiment of the present application.
  • FIG. 3 is a schematic flowchart of another shooting control method according to an embodiment of the present application.
  • FIG. 4 is a schematic block diagram of a terminal according to an embodiment of the present application.
  • FIG. 5 is a schematic block diagram of another terminal according to an embodiment of the present application.
  • the shooting control method provided in the embodiment of the present application may be executed by a terminal, and the terminal may be a smart terminal such as a mobile phone, a computer, a tablet, or a smart watch, and the terminal is provided with a camera device.
  • the terminal may be a smart terminal such as a mobile phone, a computer, a tablet, or a smart watch, and the terminal is provided with a camera device.
  • the following describes the shooting control method for the terminal.
  • the terminal in the process of taking a picture by using the camera device, the terminal may first use the camera device of the terminal to collect a preview image, and after obtaining the preview image collected by the camera device, it may detect whether the preview image exists For the shooting object, if it is detected that there is no shooting object in the preview image, the preview image can be converted into a grayscale image through image processing.
  • the terminal can obtain the gray level of each pixel point in the gray image according to the converted gray image, and determine each gray level interval of the gray image according to each gray level of the gray image.
  • the terminal may determine a cumulative probability according to a sum of distribution probabilities of grayscales in each grayscale interval, and adjust the grayscale according to a cumulative probability of each grayscale interval. It can adjust the exposure of the image, and use the adjusted exposure to perform image shooting, so as to achieve dynamic adjustment of the image exposure, enhance the image contrast, and improve the clarity of the captured image.
  • the shooting control method provided by the embodiment of the present application will be described below with reference to the drawings.
  • FIG. 1 is a schematic flowchart of a shooting control method according to an embodiment of the present application. As shown in FIG. 1, the method may be executed by a terminal. The specific explanation of the terminal is as described above, and is not described here. More details. Specifically, the method in the embodiment of the present application includes the following steps.
  • the terminal may obtain a preview image collected by the camera device, and after acquiring the preview image, it may detect whether a photographic object exists in the preview image collected by the camera device of the terminal. If there is a subject, the preview image can be converted into a grayscale image.
  • the photographic subject may be an object composed of any one or more things, such as a human body, a human face, an object, and the embodiment of the present application does not specifically limit the composition of the photographic subject.
  • the terminal when the terminal detects whether there is a photographic subject in the preview image collected by the camera device of the terminal, the terminal may perform an operation on the acquired terminal according to the preview image collected by the camera device of the terminal.
  • the preview image collected by the camera device is subjected to image processing to obtain the blur degree of the preview image. If it is detected that the blur degree of the preview image is greater than a preset blur degree threshold value, it is determined that There is no subject in the preview image.
  • the method for obtaining the blur degree of the preview image by the terminal may be obtained by processing the preview image by using various existing methods, which are not specifically limited in the embodiment of the present application.
  • the terminal detects whether there is a shooting object in the preview image collected by the camera device of the terminal, the terminal obtains the acquired image according to the preview image collected by the camera device of the terminal.
  • the blur degree of the preview image obtained by performing image processing on the preview image collected by the camera device of the terminal is m, and if it is detected that the blur degree m of the preview image is greater than a preset blur threshold k, it may be determined There is no shooting subject in the preview image collected by the camera device of the terminal.
  • the terminal when the terminal detects whether a photographic subject exists in the preview image collected by the camera device of the terminal, it can also detect whether the photographic subject exists in the preview image according to a preset image recognition algorithm.
  • the preset image recognition algorithm includes any one or more algorithms such as face recognition, human body recognition, and object recognition. The embodiments of the present application do not specifically limit the preset image algorithm.
  • the terminal can use the face recognition algorithm to detect whether a face exists in the preview image collected by the camera device of the terminal. ; And detecting the presence of a human body in the preview image collected by the terminal camera device through the human body recognition algorithm; and detecting the presence of the photographed object in the preview image collected by the terminal camera device through a preset object recognition algorithm;
  • the algorithm does not recognize any subjects such as faces, human bodies, and objects in the preview image, so it can be determined that no subjects can be detected from the preview image.
  • the terminal when the terminal converts the preview image into a grayscale image, the terminal may obtain the GBR brightness value of each pixel point in the preview image and calculate the grayscale value Gray of each pixel point of the preview image according to the following formula,
  • R is a red brightness value
  • G is a green brightness value
  • B is a blue brightness value.
  • the terminal may determine the grayscale image corresponding to the preview image according to the grayscale value of each pixel in the preview image calculated by the foregoing formula.
  • the terminal may uniformly replace R, G, and B in the RGB (R, G, B) obtained in the preview image with the corresponding gray value Gray to form a new color RGB (Gray, Gray, Gray). ), Use it to replace the original RGB (R, G, B) to get the grayscale image corresponding to the preview image.
  • S102 Determine the distribution probability of the gray level of each pixel and each gray level interval of the gray image according to the gray level of each pixel in the gray image.
  • the terminal may obtain a gray level of each pixel in the gray image according to the gray image, and determine each pixel according to the gray level of each pixel in the gray image that is obtained.
  • the distribution probability of the gray level and each gray level interval of the gray image may be obtained.
  • the terminal when determining the distribution probability of the gray level of each pixel according to the gray level of each pixel in the gray image, the terminal may obtain each pixel in the gray image by And determine the gray levels of each pixel according to the obtained gray values of each pixel, and according to the total number of pixels in the gray image and the pixels corresponding to each gray level Number to determine the distribution probability of each gray level.
  • the distribution probability can be calculated by the following formula:
  • the P (r k) represents the probability distribution of the gray level r k
  • r k is the gray scales corresponding to the number of pixels r k n divided by the total number of pixels in the gray scale image to obtain a gray level r k is a probability distribution P (r k).
  • the terminal may determine a normalized gray histogram according to the distribution probability corresponding to each gray level, for the user to view Through this normalized histogram, the distribution probability of each gray level can be viewed more directly.
  • the terminal can use The number of pixels n corresponding to each gray level obtained and the total number N of pixels in the gray image obtained, the number of pixels n corresponding to each gray level and the pixels in the gray image obtained are calculated The ratio n / N of the total number N of points is determined as the distribution probability of each gray level of the gray image.
  • the terminal when the terminal determines each gray level interval of the gray image according to the gray level of each pixel point in the gray image obtained, the terminal may Divide the interval to obtain one or more gray-level intervals.
  • the gray level represents the maximum number of different gray values in a gray image.
  • the larger the gray level the larger the brightness range of the image.
  • the gray value range of a gray image is [0,255], so there are 256 levels in total.
  • the range of the gray level is [0,255], where 0 represents black and 255 represents white.
  • the gray image becomes brighter and brighter. It should be noted that because the gray level of the statistical gray image is to identify the shooting object from the adjusted gray image, the solution does not need to count the gray level interval with high contrast because the gray level with high contrast is The step section can recognize the subject.
  • the terminal may divide the gray level of the gray image into three sections according to the following preset rules, assuming that the range of gray level i is ⁇ 0,1,2 ,,,,,, L- 1 ⁇ , the gray level of the gray level interval i ⁇ [0,0.4 (L-1)] can be divided into the first statistical interval of the statistical dark image part; the gray level i ⁇ [0.6 (L-1), L-1] This gray level interval is divided into the second statistical interval of the statistical bright part; the gray level i ⁇ [0.35 (L-1), 0.65 (L-1)] is gray The degree interval is divided into a third statistical interval with a lower statistical contrast.
  • the terminal may follow a preset rule, that is, the first statistical interval is i ⁇ [0,0.4 (L-1)], the second statistical interval is i ⁇ [0.6 (L-1), L-1], and the third statistical interval is i ⁇ [0.6 (L-1), L- 1] rule, the gray level of the gray image is divided into: a first statistical interval [0,102], a second statistical interval [153,255], and a third statistical interval [89,166].
  • the division of the grayscale interval of the grayscale image may also adopt other division rules.
  • the embodiment of the present application does not specifically limit the division rule of the grayscale interval of the grayscale image.
  • S103 Adjust the exposure of the gray image according to the cumulative probability of each gray level interval, and perform image shooting according to the adjusted exposure.
  • the terminal may adjust the exposure of the grayscale image according to the acquired cumulative probability of each grayscale interval, and perform image shooting according to the adjusted exposure degree, where the cumulative probability is grayscale The sum of the distribution probabilities of the gray levels in the interval.
  • the terminal may divide the gray level of the gray image according to a preset rule according to the obtained normalized gray histogram, and obtain the cumulative probability in each statistical interval.
  • the formula for statistical cumulative probability is as follows:
  • i ⁇ [a, b] is the statistical interval
  • Pr (r i ) is the distribution probability corresponding to the gray level r k in the normalized histogram.
  • the gray level range of the grayscale image is [0,255], and according to a preset rule, the first statistical interval is i ⁇ [0,0.4 (L-1)], and the second statistical interval is i ⁇ [0.6 (L-1), L-1], and the third statistical interval is i ⁇ [0.35 (L-1), 0.65 (L-1)].
  • the gray level of this gray image is divided into: The first statistical interval [0, 102], the second statistical interval [153, 255], and the third statistical interval [89, 166], then the cumulative probability of each gray level statistical interval of the gray image can be calculated as:
  • the terminal may perform image shooting according to the adjusted exposure.
  • the terminal may convert the preview image into a grayscale image, and determine each The distribution probability of the gray levels of the pixels and each gray level interval of the gray image, the exposure of the gray image is adjusted according to the cumulative probability of each gray level interval, and the adjusted exposure and focal length are used Take an image. In this way, dynamic adjustment of image exposure can be achieved, image contrast is enhanced, and sharpness of the captured image is improved.
  • FIG. 2 is a schematic flowchart of another shooting control method according to an embodiment of the present application. As shown in FIG. 2, the method may be executed by a terminal. The specific explanation of the terminal is as described above, and is not described here. More details. The difference between the embodiment of the present application and the embodiment shown in FIG. 1 is that the embodiment of the present application mainly describes the detailed process of adjusting the exposure of the grayscale image according to the cumulative probability of each grayscale interval. Specifically, the method in the embodiment of the present application includes the following steps.
  • the terminal may detect whether a photographic subject exists in the preview image collected by the camera device of the terminal, and if it is detected that the photographic subject does not exist in the preview image, the preview image may be converted into a grayscale image.
  • the explanation of the subject is as described above, and is not repeated here.
  • S202 Determine the distribution probability of the gray level of each pixel and each gray level interval of the gray image according to the gray level of each pixel in the gray image.
  • the terminal may determine the distribution probability of the gray level of each pixel and each gray level interval of the gray image according to the gray level of each pixel in the gray image, and the determining
  • the specific implementation process and example of determining the gray level distribution probability of each pixel and determining each gray level interval of the gray image are as described above, and are not repeated here.
  • step S203 Detect whether there is a grayscale interval with a cumulative probability greater than a preset threshold in each grayscale interval. If the detection result is yes, step S204 is performed, and if the detection result is no, step S206 is performed.
  • the terminal may determine the cumulative probability based on the sum of the distribution probabilities of the gray levels in each gray level interval of the obtained gray image, and may detect whether there is a cumulative probability greater than A threshold gray level interval is set. If it is detected that a gray level interval in which the cumulative probability is greater than a preset threshold exists in each gray level interval, step S204 is performed.
  • the gray level interval obtained according to the preset rule includes: the cumulative probability of the first statistical interval is 0.88, the cumulative probability of the second statistical interval is 0.9, and the cumulative of the third statistical interval If the probability is 0.82, it can be determined that the cumulative probability of the first statistical interval and the second statistical interval in each gray level interval is greater than a preset threshold.
  • S204 Determine the target value of the exposure corresponding to the cumulative probability greater than the preset threshold in each gray level interval according to the corresponding relationship between the preset cumulative probability and the exposure.
  • the terminal may determine each gray level according to a correspondence relationship between the preset cumulative probability and exposure.
  • the target value of the exposure corresponding to the cumulative probability greater than the preset threshold in the step interval Specifically, it can be illustrated that if the exposure of the cumulative probability x obtained is n, the target value of the exposure corresponding to the cumulative probability x can be determined from the corresponding relationship according to a preset correspondence between the cumulative probability and the exposure. Is m.
  • S205 Adjust the exposure of the gray level interval in which the cumulative probability is greater than a preset threshold in the gray image to the target value.
  • the terminal may change the gray level.
  • the exposure degree of the gray level interval in which the cumulative probability is greater than a preset threshold in the image is adjusted to the target value. Specifically, for example, it is assumed that the target value of the exposure corresponding to the cumulative probability x is determined from the preset correspondence between the cumulative probability and the exposure. If the acquired exposure corresponding to the cumulative probability x in the grayscale image is obtained If the degree is n and n is greater than m, the terminal can adjust the exposure corresponding to the cumulative probability x in the grayscale image from n to m.
  • the terminal may perform image shooting according to the adjusted exposure.
  • the terminal when the terminal detects that there is no shooting object in the preview image collected by the camera device, the terminal converts the preview image into a grayscale image, and determines the distribution probability of the grayscale level of each pixel and the Each gray level interval of the gray image, and the cumulative probability is determined according to the sum of the distribution probability of the gray levels in each gray level interval of the obtained gray image. If it is detected that the gray level interval exists, For a gray level interval whose cumulative probability is greater than a preset threshold, the exposure of the gray level interval whose cumulative probability is greater than the preset threshold is adjusted to the target value, and according to the adjusted exposure Take an image. In this way, dynamic adjustment of image exposure can be achieved, image contrast is enhanced, and sharpness of the captured image is improved.
  • FIG. 3 is a schematic flowchart of another shooting control method according to an embodiment of the present application. As shown in FIG. 3, the method may be executed by a terminal. The specific explanation of the terminal is as described above, and is not described here. More details. The difference between the embodiment of the present application and the embodiment shown in FIG. 2 is that the embodiment of the present application can also adjust the focal length of the imaging device according to the position information of the shooting object in the grayscale image. Specifically, the method in the embodiment of the present application includes the following steps.
  • the terminal may detect whether a photographic subject exists in the preview image collected by the camera device of the terminal, and if it is detected that the photographic subject does not exist in the preview image, the preview image may be converted into a grayscale image.
  • the explanation of the subject is as described above, and is not repeated here.
  • S302 Determine the distribution probability of the gray level of each pixel and each gray level interval of the gray image according to the gray level of each pixel in the gray image.
  • the terminal may determine the distribution probability of the gray level of each pixel and each gray level interval of the gray image according to the gray level of each pixel in the gray image, and the determining
  • the specific implementation process and example of determining the gray level distribution probability of each pixel and determining each gray level interval of the gray image are as described above, and are not repeated here.
  • S303 Adjust the exposure of the grayscale image according to the cumulative probability of each grayscale interval.
  • the terminal may determine the cumulative probability according to the sum of the distribution probabilities of the gray levels in each gray level interval of the gray image obtained, where the interpretation of the cumulative probability is as described above, here No longer.
  • S304 Perform equalization processing on the grayscale image according to a distribution probability of each grayscale level.
  • the terminal may further perform equalization processing on the grayscale image according to the obtained distribution probability of the grayscale image.
  • the terminal may determine a cumulative probability histogram of the grayscale image according to the distribution probability of each grayscale level, and use the cumulative probability histogram according to the A histogram equalization processing technique performs contrast enhancement processing on the grayscale image.
  • the histogram equalization process is a transformation function that can automatically achieve the effect that the pixels of the image occupy a lot of gray levels and are evenly distributed by using only the histogram information of the input image.
  • the terminal may determine the cumulative probability histogram according to the obtained normalized grayscale histogram.
  • the distribution probability of the gray value r i normalized to the interval [0,1] is P (r i ), and r 0 represents black, and r L-1 represents white; then E k (k ) Satisfy the following two conditions:
  • This embodiment performs equalization processing on a grayscale image by determining a cumulative probability histogram.
  • the grayscale value is normalized to an interval [0,1] to ensure a one-to-one correspondence between input and output.
  • the interval [0 1] Monotonic increase ensures the corresponding order of grayscale images from black to white, and does not appear reverse grayscale, thereby ensuring that the input and output are in the same range.
  • the mapping of the probability cumulative to the gray space can be obtained through (L-1) E k (k), thereby achieving the equalization processing of the gray image.
  • Such equalization processing can make the gray value cover a larger range of the gray level and improve the sharpness of the gray image.
  • the terminal when the terminal uses the histogram equalization processing technology to perform contrast enhancement processing on the grayscale image according to the cumulative probability histogram, the terminal may adjust according to the cumulative probability histogram according to a preset rule.
  • the cumulative probability of each grayscale interval in the grayscale image is adjusted according to the cumulative probability of each grayscale interval after adjustment, the grayscale value of each grayscale interval corresponding to each pixel in the grayscale image, To enhance the contrast of the grayscale image.
  • S305 Determine position information of the shooting object from the grayscale image after the equalization process.
  • the terminal may determine position information of the shooting object from the grayscale image after the equalization process.
  • the terminal can detect the grayscale image after the equalization processing according to a preset detection algorithm such as a face recognition algorithm, a human detection algorithm, an object detection algorithm, and the like, and obtain the shooting object in the grayscale image.
  • a preset detection algorithm such as a face recognition algorithm, a human detection algorithm, an object detection algorithm, and the like.
  • Coordinate position information such as P (x, y).
  • S306 Adjust the focal length of the imaging device according to the position information of the photographic subject in the grayscale image after the equalization process, and use the adjusted exposure and focal length to perform image shooting.
  • the terminal when the terminal adjusts the focal length of the imaging device according to the position information of the photographic object in the grayscale image, the terminal may use the position information of the photographic object in the grayscale image after the equalization process. , Adjusting the focal length of the imaging device, and using the adjusted exposure and focal length for image capture.
  • the terminal when the terminal adjusts the focal length of the imaging device according to the position information of the photographic object in the grayscale image after the equalization process, the terminal may use the acquired coordinates of the photographic object in the grayscale image.
  • Position information such as P (x, y), adjusts the focal length of the camera.
  • the focusing process of the imaging device is to send the acquired coordinate position information of the photographic object in the grayscale image to the imaging device, so that the imaging device adjusts the focal length of the imaging device according to a preset focusing algorithm.
  • the embodiment of the present application does not specifically limit the preset focusing algorithm. In this way, the grayscale image can be made clearer, the focus of the camera device can be more accurate, and a sharper subject can be obtained.
  • the terminal when the terminal detects that there is no shooting object in the preview image collected by the camera device, the terminal converts the preview image into a grayscale image, and determines the distribution probability of the grayscale level of each pixel and the Each grayscale interval of the grayscale image, and adjusting the exposure of the grayscale image according to the cumulative probability of each grayscale interval, and performing equalization processing on the grayscale image,
  • the position information of the photographic subject is determined in the image
  • the focal length of the imaging device is adjusted according to the position information of the photographic subject in the grayscale image after the equalization process, and the adjusted exposure and focal length are used for the image Shoot. In this way, dynamic adjustment of the focal length of the imaging device can be achieved, and the sharpness of the captured image is further improved.
  • FIG. 4 is a schematic block diagram of a terminal provided by an embodiment of the present application.
  • the terminal in this embodiment includes a first detection unit 401, a conversion unit 402, a determination unit 403, and a first adjustment unit 404.
  • the first detection unit 401 is configured to detect whether a photographing object exists in a preview image collected by the camera device of the terminal.
  • the first detection unit 401 is specifically configured to perform image processing on the acquired preview image collected by the camera device of the terminal to obtain the blur degree of the preview image; if the blur degree of the preview image is detected If it is larger than the preset blurriness threshold, it is determined that there is no shooting object in the preview image collected by the camera device of the terminal.
  • the conversion unit 402 is configured to convert the preview image into a grayscale image if it is detected that there is no shooting object in the preview image collected by the camera device of the terminal.
  • a determining unit 403 is configured to determine a distribution probability of a gray level of each pixel and each gray level interval of the gray image according to a gray level of each pixel in the gray image.
  • a determining unit 403 is configured to obtain a gray value of each pixel in the gray image; determine a gray level of each pixel according to the gray value of each pixel; and according to the gray image The total number of pixels and the number of pixels corresponding to each gray level determine the distribution probability of each gray level; each gray level is divided into intervals according to a preset division rule to obtain one or more gray level intervals.
  • the terminal in the embodiment of the present application further includes: a second detection unit 406,
  • a second detection unit 406 is configured to detect whether there is a gray level with a cumulative probability greater than a preset threshold in each gray level interval before adjusting the exposure of the gray image according to the cumulative probability of each gray level interval. Interval; if it is detected that a gray level interval in which the cumulative probability is greater than a preset threshold exists in each gray level interval, adjusting the exposure of the gray image in each gray interval according to the cumulative probability of each gray level interval degree.
  • the first adjusting unit 404 is configured to determine a target value of the exposure corresponding to the cumulative probability greater than a preset threshold in each gray level interval according to the corresponding relationship between the preset cumulative probability and the exposure; The exposure of the gray level interval with the cumulative probability greater than a preset threshold is adjusted to the target value.
  • the terminal in the embodiment of the present application further includes: a second adjustment unit 405,
  • a second adjustment unit 405 configured to perform equalization processing on the grayscale image; determine position information of the photographic object from the grayscale image after the equalization processing; and according to the photographic object after the equalization processing, Position information in the grayscale image, adjusting the focal length of the camera device in the terminal, and using the adjusted exposure and focal length for image capture.
  • a second adjusting unit 405 is configured to determine a cumulative probability histogram of the grayscale image according to the distribution probability of each grayscale level; and adjust the grayscale image according to a preset rule according to the cumulative probability histogram.
  • the cumulative probability of each gray level interval in the medium according to the cumulative probability of each gray level interval after adjustment, adjusting the gray value of each gray level interval corresponding to each pixel in the gray image to enhance the gray level Degree image contrast.
  • the preview image may be converted into a grayscale image by the conversion unit 402, and the determination unit 403 may convert Gray level of each pixel in the image, determines the distribution probability of the gray level of each pixel and each gray level interval of the gray image, and the first adjusting unit 404 adjusts according to the cumulative probability of each gray level interval
  • the second adjustment unit 405 adjusts the focal length of the imaging device according to the position information of the photographic subject in the grayscale image, and uses the adjusted exposure and focal length to perform image shooting. In this way, dynamic adjustment of the image exposure and the focal length of the imaging device can be achieved, and the sharpness of the captured image is improved.
  • FIG. 5 is a schematic block diagram of another terminal provided by an embodiment of the present application.
  • the terminal in this embodiment as shown in the figure may include: one or more processors 501; one or more input devices 502, one or more output devices 503, and a memory 504.
  • the processor 501, the input device 402, the output device 503, and the memory 504 are connected through a bus 505.
  • the memory 504 is configured to store a computer program, where the computer program includes program instructions, and the processor 501 is configured to execute the program instructions stored in the memory 504.
  • the processor 501 is configured to call the program instruction to execute:
  • the exposure of the grayscale image is adjusted according to the cumulative probability of each grayscale interval, and image shooting is performed according to the adjusted exposure degree, where the cumulative probability is one of the distribution probability of the grayscale within the grayscale interval. with.
  • processor 501 is configured to perform the following steps:
  • the blur degree of the preview image is greater than a preset blur degree threshold, it is determined that there is no photographic subject in the preview image collected by the camera device of the terminal.
  • processor 501 is configured to perform the following steps:
  • Interval division of each gray level is performed according to a preset division rule to obtain one or more gray level intervals.
  • processor 501 is configured to perform the following steps:
  • processor 501 is configured to perform the following steps:
  • processor 501 is configured to perform the following steps:
  • processor 501 is configured to perform the following steps:
  • the gray value of each pixel point corresponding to each gray level interval in the gray image is adjusted to enhance the contrast of the gray image.
  • the terminal may convert the preview image into a grayscale image, and determine each of the grayscale levels according to the grayscale level of each pixel in the grayscale image.
  • the distribution probability of the gray levels of the pixels and each gray level interval of the gray image adjusting the exposure of the gray image according to the cumulative probability of each gray level interval, and using the adjusted exposure to perform the image Shoot. In this way, dynamic adjustment of image exposure can be achieved, image contrast is enhanced, and sharpness of the captured image is improved.
  • the processor 501 may be a central processing unit (CPU), and the processor may also be another general-purpose processor or a digital signal processor (DSP). , Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the input device 502 may include a touch panel, a fingerprint sensor (for collecting fingerprint information and orientation information of a user), a microphone, and the like, and the output device 503 may include a display (LCD, etc.), a speaker, and the like.
  • a fingerprint sensor for collecting fingerprint information and orientation information of a user
  • a microphone for collecting fingerprint information and orientation information of a user
  • the output device 503 may include a display (LCD, etc.), a speaker, and the like.
  • the memory 504 may include a read-only memory and a random access memory, and provide instructions and data to the processor 501. A part of the memory 504 may further include a non-volatile random access memory. For example, the memory 504 may also store information of a device type.
  • the processor 501, the input device 502, and the output device 503 described in the embodiments of the present application can execute the method of shooting control provided in the embodiments of the present application in the method embodiments shown in FIG. 1, FIG. 2, or FIG. 3.
  • the described implementation manner may also implement the implementation manner of the terminal described in FIG. 4 in the embodiment of the present application, and details are not described herein again.
  • a computer-readable storage medium is also provided in the embodiments of the present application.
  • the computer-readable storage medium stores a computer program, and the computer program implements the embodiments corresponding to FIG.
  • the shooting control method described in the above can also implement the terminal of the embodiment corresponding to FIG. 4 or FIG. 5 of the present application, and details are not described herein again.
  • the computer-readable storage medium may be an internal storage unit of the terminal according to any of the foregoing embodiments, such as a hard disk or a memory of the terminal.
  • the computer-readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), and a Secure Digital (SD) card provided on the terminal. , Flash card (Flash card) and so on.
  • the computer-readable storage medium may further include both an internal storage unit of the terminal and an external storage device.
  • the computer-readable storage medium is used to store the computer program and other programs and data required by the terminal.
  • the computer-readable storage medium may also be used to temporarily store data that has been or will be output.

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Abstract

本申请实施例公开了一种拍摄控制方法、终端及计算机可读存储介质，其中方法包括：检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像；根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。通过这种方式实现了动态调节图像曝光度，增强了图像对比度，提高了拍摄图像的清晰度。

Description

一种拍摄控制方法、终端及计算机可读存储介质
本申请要求于2018年07月05日提交中国专利局、申请号为201810735397.7、申请名称为“一种拍摄控制方法、终端及计算机可读介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机技术领域，尤其涉及一种拍摄控制方法、终端及计算机可读存储介质。
背景技术
目前移动终端、智能手表、平板电脑、机器人等智能终端的功能越来越多，其中，最基本的且用户使用较多的一项功能是智能终端的摄像装置的拍照功能。然而，在用户通过智能终端的摄像装置进行拍照的过程中，往往由于环境光照的变化，导致无法正常识别出拍摄对象。因此，如何更有效地提高各种环境下的拍摄效果成为研究的热点。
发明内容
本申请实施例提供一种拍摄控制方法、终端及计算机可读存储介质，可实现动态调节图像曝光度，增强了图像对比度，提高了拍摄图像的清晰度。
第一方面，本申请实施例提供了一种拍摄控制方法，该方法包括：
检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；
如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像；
根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；
根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
第二方面，本申请实施例提供了一种终端，该终端包括用于执行上述第一方面的方法的单元。
第三方面，本申请实施例提供了另一种终端，包括处理器、输入设备、输出设备和存储器，所述处理器、输入设备、输出设备和存储器相互连接，其中，所述存储器用于存储支持终端执行上述方法的计算机程序，所述计算机程序包括程序指令，所述处理器被配置用于调用所述程序指令，执行上述第一方面的方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，所述计算机存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令当被处理器执行时使所述处理器执行上述第一方面的方法。
本申请实施例，根据灰度图像中各像素点的灰度级的分布概率和各灰度级区间的累计概率调整图像曝光度，实现了对图像曝光度的动态调节，增强了图像对比度，提高了拍摄图像的清晰度。
附图说明
图1是本申请实施例提供的一种拍摄控制方法的示意流程图；
图2是本申请实施例提供的另一种拍摄控制方法的示意流程图；
图3是本申请实施例提供的又一种拍摄控制方法的示意流程图；
图4是本申请实施例提供的一种终端的示意框图；
图5是本申请实施例提供的另一种终端示意框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
应当理解，在此本申请说明书中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本申请。如在本申请说明书和所附权利要求书中所使用的那样，除非上下文清楚地指明其它情况，否则单数形式的“一”、“一个”及“该”意在包括复数形式。
还应当进一步理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
本申请实施例提供的拍摄控制方法可以由终端执行，所述终端可以是手机、电脑、平板、智能手表等智能终端，该终端上设置有摄像装置。下面对应用于终端的拍摄控制方法进行说明。
本申请实施例中，终端在利用摄像装置进行拍照的过程中，首先可以利用该终端的摄像装置采集预览图像，在获取到该摄像装置采集到的预览图像之后，可以检测该预览图像中是否存在拍摄对象，如果检测到该预览图像中不存在拍摄对象，则可以通过图像处理将该预览图像转化为灰度图像。该终端可以根据转化得到的灰度图像获取到该灰度图像中各像素点的灰度级，并根据该灰度图像的各灰度级确定该灰度图像的各灰度级区间。在确定该灰度图像的各灰度级区间之后，该终端可以根据各灰度级区间内的 灰度级的分布概率之和确定累计概率，并根据各灰度级区间的累计概率调整该灰度图像的曝光度，并采用调整后的曝光度进行图像拍摄，从而实现动态调节图像曝光度，增强了图像对比度，提高了拍摄图像的清晰度。下面结合附图对本申请实施例提供的拍摄控制方法进行说明。
参见图1，图1是本申请实施例提供的一种拍摄控制方法的示意流程图，如图1所示，该方法可以由终端执行，所述终端的具体解释如前所述，此处不再赘述。具体地，本申请实施例的所述方法包括如下步骤。
S101：如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像。
本申请实施例中，终端可以获取摄像装置采集到的预览图像，在获取到预览图像之后可以检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象，如果检测到该预览图像中不存在拍摄对象，则可以将该预览图像转化为灰度图像。其中，所述拍摄对象可以是由人体、人脸、物体等任意一种或多种事物组成的对象，本申请实施例对拍摄对象的组成不做具体限定。
在一个实施例中，该终端在检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象时，可以根据所述终端的摄像装置采集到的预览图像，对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度，如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。其中，该终端获取预览图像的模糊度的方法可以采用现有的多种方法对该预览图像进行处理得到，本申请实施例不做具体限定。
例如，假设预设的模糊度阈值为k，如果终端在检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象时，根据所述终端的摄像装置采集到的预览图像，对获取到的所述终端的摄像装置采集到的预览图像进行图像处理得到的所述预览图像的模糊度为m，如果检测到所述预览图像的模糊度m大于预设的模糊度阈值k，则可以确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
在一个实施例中，该终端在检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象时，还可以根据预设的图像识别算法检测该预览图像中是否存在拍摄对象。其中，该预设的图像识别算法包括人脸识别、人体识别、物体识别等任意一种或多种算法，本申请实施例对该预设的图像算法不做具体限定。
具体可以举例说明，假设预设的图像识别算法包括人脸识别算法、人体识别算法和物体识别算法，则该终端可以通过该人脸识别算法检测终端摄像装置采集到的预览图像中是否存在人脸；以及通过该人体识别算法检测终端摄像装置采集到的预览图像中是否存在人体；以及通过预设的物体识别算法检测终端摄像装置采集到的预览图像中是否存在被拍摄物体；如果通过上述各识别算法均没有识别出该预览图 像中存在任何人脸、人体、物体等拍摄对象，则可以确定从该预览图像中检测不到拍摄对象。
在一个实施例中，终端在将所述预览图像转化为灰度图像时，可以通过获取预览图像中各个像素点的GBR亮度值，根据以下公式计算该预览图像各个像素点的灰度值Gray，
Gray＝(R*299+G*587+B*114+500)/1000
其中，R为红色亮度值、G为绿色亮度值、B为蓝色亮度值。
终端可以根据上述公式计算得到的预览图像中各个像素点的灰度值，确定出该预览图像对应的灰度图像。具体实施过程中，终端可以将预览图像中获取到的RGB(R，G，B)中的R、G、B统一用对应的灰度值Gray替换，形成新的颜色RGB(Gray，Gray，Gray)，用它替换原来的RGB(R，G，B)得到与该预览图像对应的灰度图。
S102：根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间。
本申请实施例中，终端可以根据所述灰度图像获取该灰度图像中各像素点的灰度级，并根据获取到的该灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间。
在一个实施例中，终端在根据获取到的该灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率时，可以通过获取所述灰度图像中各像素点的灰度值，并根据获取到的各像素点的灰度值，确定各像素点的各灰度级，以及根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率。其中，该分布概率可以利用如下公式计算得到：
P(r k)＝n k/n k＝0,1,......,L-1
其中，该P(r k)表示灰度级r k的分布概率，用灰度级为r k对应的像素点数量r k除以该灰度图像的像素点的总数量n，得到灰度级r k的分布概率为P(r k)。
在一个实施例中，终端在计算得到该灰度图像中各灰度级对应的分布概率后，可以根据各个灰度级对应的分布概率，确定出归一化的灰度直方图，以便用户查看，通过该归一化的直方图可以更直接地查看各灰度级的分布概率。所述归一化的灰度直方图是指由各个灰度级对应的分布概率组成的灰度直方图，即该归一化的灰度直方图中的所有灰度级对应的分布概率之和为1，即p(r 0)+p(r 1)+p(r 2)+p(r 3)+…+p(r L-1)＝1。其中，需要说明的是，归一化灰度直方图的横坐标为灰度级r k，纵坐标为P(rk)。
具体可举例说明，假设终端获取到该灰度图像中像素点的总数量为N，根据确定的各像素点的各灰度级获取各灰度级对应的像素点数量为n，则终端可以利用获取到的各灰度级对应的像素点数量n以及获取到的该灰度图像中像素点的总数量N，计算各灰度级对应的像素点数量n与获取到的该灰度图像 中像素点的总数量N的比值n/N，将得到的该比值n/N确定为该灰度图像各灰度级的分布概率。
在一个实施例中，终端在根据获取到的该灰度图像中各像素点的灰度级，确定所述灰度图像的各灰度级区间时，可以按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。其中，灰度级表示灰度图像中不同灰度值的最大数量，灰度级越大，图像的亮度范围越大。一般灰度图像的灰度值范围为[0，255]，因此灰度级总共有256级。灰度级的范围为[0，255]，0代表黑色，255代表白色，随着灰度级的增加灰度图像越来越亮。需要说明的是，由于统计灰度图像的灰度级是为了从调整后的灰度图像中识别出拍摄对象，因此本方案不需要统计对比度很高的灰度级区间，因为对比度高的灰度级区间能够识别出拍摄对象。
在一个实施例中，终端可以按照以下预设的规则对该灰度图像的灰度级划分为三个区间，假设灰度级i的范围为{0,1,2,、、、,L-1}，则可以将灰度级i∈[0,0.4(L-1)]这个灰度级区间的灰度级划分为统计暗图部分的第一统计区间；将灰度级i∈[0.6(L-1),L-1]这个灰度级区间划分为统计亮图部分的第二统计区间；将灰度级i∈[0.35(L-1),0.65(L-1)]这个灰度级区间划分为统计对比度较低的第三统计区间。具体可举例说明，假设获取到的灰度图像的灰度级i的范围为{0,1,2,、、、,L-1}，则终端可以按照预设的规则即第一统计区间为i∈[0,0.4(L-1)]，第二统计区间为i∈[0.6(L-1),L-1]，第三统计区间为i∈[0.6(L-1),L-1]的规则，将该灰度图像的灰度级划分为：第一统计区间[0，102]、第二统计区间[153，255]、第三统计区间[89，166]。当然，在其他实施例中，该灰度图像的灰度级区间的划分还可以采用其他划分规则，本申请实施例对灰度图像的灰度级区间的划分规则不做具体的限定。
S103：根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄。
本申请实施例中，终端可以根据获取到的各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
在一个实施例中，终端可以根据得到的归一化灰度直方图，按照预设的规则对灰度图像的灰度级进行划分，得到的各统计区间内的累计概率。其中，统计累计概率的公式如下：
Figure PCTCN2018108677-appb-000001
其中，i∈[a,b]为统计区间，Pr(r i)为归一化直方图中灰度级r k对应的分布概率。
具体可举例说明，假设灰度图的灰度级范围为[0，255]，且按照预设的规则第一统计区间为i∈[0,0.4(L-1)]，第二统计区间为i∈[0.6(L-1),L-1]，第三统计区间为i∈[0.35(L-1),0.65(L-1)]，将该灰度图像 的灰度级划分为：第一统计区间[0，102]、第二统计区间[153，255]、第三统计区间[89，166]，则可以计算得到该灰度图像各灰度级统计区间的累计概率为：
S k＝p(r 0)+…+p(r 102) k＝0,1,…,102；
S k＝p(r 153)+…+p(r 255) k＝153,154,…,255；
S k＝p(r 89)+…+p(r 166) k＝89,90,…,166。
在一个实施例中，终端可以在根据各灰度级区间的累计概率调整所述灰度图像的曝光度后，按照调整后的曝光度进行图像拍摄。
本申请实施例，终端如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则可以将预览图像转化为灰度图像，根据灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并采用调整后的曝光度和焦距进行图像拍摄。通过这种方式可以实现对图像曝光度的动态调节，增强了图像对比度，提高了拍摄图像的清晰度。
参见图2，图2是本申请实施例提供的另一种拍摄控制方法的示意流程图，如图2所示，该方法可以由终端执行，该终端的具体解释如前所述，此处不再赘述。本申请实施例与上述图1所述实施例的区别在于，本申请实施例主要讲述是根据各灰度级区间的累计概率调整所述灰度图像的曝光度的详细过程。具体地，本申请实施例的所述方法包括如下步骤。
S201：如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像。
本申请实施例中，终端可以检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象，如果检测到该预览图像中不存在拍摄对象，则可以将该预览图像转化为灰度图像。其中，所述拍摄对象的解释如前所述，此处不再赘述。
S202：根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间。
本申请实施例中，终端可以根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，所述确定各像素点的灰度级的分布概率以及确定所述灰度图像的各灰度级区间的具体实施过程和举例如前所述，此处不再赘述。
S203：检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间，如果检测结果为是，则执行步骤S204，如果检测结果为否，则执行步骤S206。
本申请实施例中，终端可以根据获取到的该灰度图像的各灰度级区间内灰度级的分布概率之和确定累计概率，并可以检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间，如果检测到各 灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行步骤S204。例如，假设预设阈值为0.85，如果根据预设的规则划分得到的灰度级区间包括：第一统计区间的累计概率为0.88、第二统计区间的累计概率为0.9、第三统计区间的累计概率为0.82，则可以确定各灰度级区间中的第一统计区间和第二统计区间的累计概率大于预设阈值。
S204：根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值。
本申请实施例中，终端在检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间后，可以根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值。具体可举例说明，假设获取到的累计概x的曝光度为n，则可以根据预设的累计概率与曝光度的对应关系，从该对应关系中确定出累计概率x对应的曝光度的目标值为m。
S205：将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。
本申请实施例中，终端在根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值后，可以将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。具体可举例说明，假设从预设的累计概率与曝光度的对应关系中确定出累计概率x对应的曝光度的目标值为m，如果获取到的该灰度图像中的累计概率x对应的曝光度为n，且n大于m，则该终端可以将灰度图像中的累计概率x对应的曝光度从n调整至m。
S206：按照调整后的曝光度进行图像拍摄。
本申请实施例中，终端在将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值之后，可以按照调整后的曝光度进行图像拍摄。
本申请实施例中，终端在检测到摄像装置采集到的预览图像中不存在拍摄对象时，通过将该预览图像转化为灰度图像，以及确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，并根据获取到的该灰度图像的各灰度级区间内灰度级的分布概率之和确定累计概率，如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值，并按照调整后的曝光度进行图像拍摄。通过这种方式可以实现对图像曝光度的动态调节，增强了图像对比度，提高了拍摄图像的清晰度。
参见图3，图3是本申请实施例提供的又一种拍摄控制方法的示意流程图，如图3所示，该方法可以由终端执行，该终端的具体解释如前所述，此处不再赘述。本申请实施例与上述图2所述实施例的区别在于，本申请实施例还可以对根据所述灰度图像中所述拍摄对象的位置信息调整所述摄像装置的焦距。具体地，本申请实施例的所述方法包括如下步骤。
S301：如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像。
本申请实施例中，终端可以检测该终端的摄像装置采集到的该预览图像中是否存在拍摄对象，如果检测到该预览图像中不存在拍摄对象，则可以将该预览图像转化为灰度图像。其中，所述拍摄对象的解释如前所述，此处不再赘述。
S302：根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间。
本申请实施例中，终端可以根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，所述确定各像素点的灰度级的分布概率以及确定所述灰度图像的各灰度级区间的具体实施过程和举例如前所述，此处不再赘述。
S303：根据各灰度级区间的累计概率调整所述灰度图像的曝光度。
本申请实施例中，终端可以根据获取到的该灰度图像的各灰度级区间内灰度级的分布概率之和确定累计概率，其中，所述累计概率的解释如前所述，此处不再赘述。
S304：根据各灰度级的分布概率，对所述灰度图像进行均衡化处理。
本申请实施例中，终端还可以根据获取到的所述灰度图像的分布概率，进一步对所述灰度图像进行均衡化处理。
其中，所述终端在对所述灰度图像进行均衡化处理时，可以根据各灰度级的分布概率，确定所述灰度图像的累计概率直方图，并根据所述累计概率直方图，采用直方图均衡化处理技术对所述灰度图像进行对比度增强处理。其中，该直方图均衡化处理是一种能仅靠输入图像直方图信息自动达到图像的像素占有很多的灰度级而且分布均匀这种效果的变换函数。在一个实施例中，终端在对获取到的灰度图像进行均衡化处理时，可以根据获取到的归一化灰度直方图确定出累计概率直方图。
具体可以举例说明，假设获取到的灰度图像有L个灰度级，利用获取到的归一化灰度直方图中各灰度级的累计概率，可以确定出累积概率直方图E k(k)
Figure PCTCN2018108677-appb-000002
其中，如前所述灰度值r i被归一化到区间[0,1]的分布概率为P(r i)，且r 0表示黑色，r L-1表示白色；则E k(k)满足以下两个条件：
(a)E k(k)在区间[0,1]中为单值且单调递增
(b)当在区间[0,1]时，E k(k)∈[0,1]
该实施方式通过确定累计概率直方图的方式对灰度图像进行均衡化处理，其中，灰度值被归一化到区间[0,1]保证了输入与输出一一对应的关系，区间[0,1]单调递增保证了灰度图像从黑到白的对应顺序，不会出现反转灰度级，从而保证了输入输出在同一个范围。根据概率累计直方图这两个条件，可以通过(L-1)E k(k)可以得到概率累积到灰度空间的映射，从而实现对灰度图像的均衡化处理。这样的均衡化处理可以使灰度值覆盖整个灰度级更大的范围，提高灰度图像的清晰度。
在一个实施例中，该终端在根据所述累计概率直方图，采用直方图均衡化处理技术对所述灰度图像进行对比度增强处理时，可以根据所述累计概率直方图，按照预设规则调整所述灰度图像中各灰度级区间的累计概率，按照调整后各灰度级区间的累计概率，对所述灰度图像中各灰度级区间对应各像素点的灰度值进行调整，以增强所述灰度图像的对比度。
S305：从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息。
本申请实施例中，终端可以从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息。具体实施过程中，该终端可以根据预设的检测算法如人脸识别算法、人体检测算法、物体检测算法等，对均衡化处理后的灰度图像进行检测，得到拍摄对象在灰度图像中的坐标位置信息如P(x,y)。
S306：根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
本申请实施例中，终端在根据所述灰度图像中所述拍摄对象的位置信息调整所述摄像装置的焦距时，可以根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
在一个实施例中，终端在根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述摄像装置的焦距时，可以根据获取到的拍摄对象在灰度图像中的坐标位置信息如P(x,y)，调节摄像装置的焦距。其中，对摄像装置的调焦过程是将获取到的拍摄对象在灰度图像中的坐标位置信息发送给摄像装置，以使摄像装置根据预设的调焦算法，对摄像装置的焦距进行调整。其中，本申请实施例对该预设的调焦算法不做具体的限定。通过这种方式可以使该灰度图像更加清晰，使得摄像装置对焦更加准确，从而获取到更加清晰的拍摄对象。
本申请实施例中，终端在检测到摄像装置采集到的预览图像中不存在拍摄对象时，通过将该预览图像转化为灰度图像，以及确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，并根据各灰度级区间的累计概率调整所述灰度图像的曝光度，以及对所述灰度图像进行均衡化处理，从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息，根据所述拍摄对象在均衡化处理后的灰度图像中 的位置信息，调整所述摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。通过这种方式可以实现对摄像装置的焦距的动态调节，进一步地提高了拍摄图像的清晰度。
本申请实施例还提供了一种终端，该终端用于执行前述任一项所述的方法的单元。具体地，参见图4，图4是本申请实施例提供的一种终端的示意框图。本实施例的终端包括：第一检测单元401、转化单元402、确定单元403、第一调整单元404。
第一检测单元401，用于检测终端的摄像装置采集到的预览图像中是否存在拍摄对象。
进一步地，第一检测单元401，具体用于对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度；如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
转化单元402，用于如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像。
确定单元403，用于根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间。
进一步地，确定单元403，用于获取所述灰度图像中各像素点的灰度值；根据各像素点的灰度值，确定各像素点的各灰度级；根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率；按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。
进一步地，本申请实施例的终端还包括：第二检测单元406，
第二检测单元406，用于在所述根据各灰度级区间的累计概率调整所述灰度图像的曝光度之前，检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间；如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度。
第一调整单元404，用于根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值；将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。
进一步地，本申请实施例的终端中还包括：第二调整单元405，
第二调整单元405，用于对所述灰度图像进行均衡化处理；从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息；根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述终端中摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
进一步地，第二调整单元405，用于根据各灰度级的分布概率，确定所述灰度图像的累计概率直方 图；根据所述累计概率直方图，按照预设规则调整所述灰度图像中各灰度级区间的累计概率；按照调整后各灰度级区间的累计概率，对所述灰度图像中各灰度级区间对应各像素点的灰度值进行调整，以增强所述灰度图像的对比度。
本申请实施例，终端的第一检测单元401如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则可以通过转化单元402将预览图像转化为灰度图像，确定单元403根据灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，第一调整单元404根据各灰度级区间的累计概率调整所述灰度图像的曝光度，第二调整单元405根据所述灰度图像中拍摄对象的位置信息调整所述摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。通过这种方式可以实现对图像曝光度和摄像装置的焦距的动态调节，提高了拍摄图像的清晰度。
参见图5，图5是本申请实施例提供的另一种终端示意框图。如图所示的本实施例中的终端可以包括：一个或多个处理器501；一个或多个输入设备502，一个或多个输出设备503和存储器504。上述处理器501、输入设备402、输出设备503和存储器504通过总线505连接。存储器504用于存储计算机程序，所述计算机程序包括程序指令，处理器501用于执行存储器504存储的程序指令。其中，处理器501被配置用于调用所述程序指令执行：
检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；
如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像；
根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；
根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
进一步地，所述处理器501用于执行如下步骤：
对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度；
如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
进一步地，所述处理器501用于执行如下步骤：
获取所述灰度图像中各像素点的灰度值；
根据各像素点的灰度值，确定各像素点的各灰度级；
根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率；
按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。
进一步地，所述处理器501用于执行如下步骤：
检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间；
如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度。
进一步地，所述处理器501用于执行如下步骤：
根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值；
将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。
进一步地，所述处理器501用于执行如下步骤：
对所述灰度图像进行均衡化处理；
从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息；
根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述终端中摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
进一步地，所述处理器501用于执行如下步骤：
根据各灰度级的分布概率，确定所述灰度图像的累计概率直方图；
根据所述累计概率直方图，按照预设规则调整所述灰度图像中各灰度级区间的累计概率；
按照调整后各灰度级区间的累计概率，对所述灰度图像中各灰度级区间对应各像素点的灰度值进行调整，以增强所述灰度图像的对比度。
本申请实施例，终端如果检测到终端的摄像装置采集到的预览图像中不存在拍摄对象，则可以将预览图像转化为灰度图像，根据灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间，根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并采用调整后的曝光度进行图像拍摄。通过这种方式可以实现对图像曝光度的动态调节，增强了图像对比度，提高了拍摄图像的清晰度。
应当理解，在本申请实施例中，所称处理器501可以是中央处理单元(Central Processing Unit，CPU)，该处理器还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
输入设备502可以包括触控板、指纹采传感器(用于采集用户的指纹信息和指纹的方向信息)、麦克风等，输出设备503可以包括显示器(LCD等)、扬声器等。
该存储器504可以包括只读存储器和随机存取存储器，并向处理器501提供指令和数据。存储器504的一部分还可以包括非易失性随机存取存储器。例如，存储器504还可以存储设备类型的信息。
具体实现中，本申请实施例中所描述的处理器501、输入设备502、输出设备503可执行本申请实施例提供的拍摄控制方法的图1、图2或图3所述的方法实施例中所描述的实现方式，也可执行本申请实施例图4所描述的终端的实现方式，在此不再赘述。
本申请实施例中还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现图1、图2或图3所对应实施例中描述的拍摄控制方法，也可实现本申请图4或图5所对应实施例的终端，在此不再赘述。
所述计算机可读存储介质可以是前述任一实施例所述的终端的内部存储单元，例如终端的硬盘或内存。所述计算机可读存储介质也可以是所述终端的外部存储设备，例如所述终端上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。进一步地，所述计算机可读存储介质还可以既包括所述终端的内部存储单元也包括外部存储设备。所述计算机可读存储介质用于存储所述计算机程序以及所述终端所需的其他程序和数据。所述计算机可读存储介质还可以用于暂时地存储已经输出或者将要输出的数据。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
以上所述，仅为本申请的部分实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。

Claims (20)

  1. 一种摄像装置的控制方法，其特征在于，包括：
    检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；
    如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像；
    根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；
    根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
  2. 根据权利要求1所述的方法，其特征在于，所述检测终端的摄像装置采集到的预览图像中是否存在拍摄对象，包括：
    对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度；
    如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
  3. 根据权利要求1所述的方法，其特征在于，所述根据所述灰度图像中各像素点的灰度级，确定各灰度级的分布概率和各灰度级区间，包括：
    获取所述灰度图像中各像素点的灰度值；
    根据各像素点的灰度值，确定各像素点的各灰度级；
    根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率；
    按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。
  4. 根据权利要求1所述的方法，其特征在于，在所述根据各灰度级区间的累计概率调整所述灰度图像的曝光度之前，还包括：
    检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间；
    如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度。
  5. 根据权利要求4所述的方法，其特征在于，所述根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度，包括：
    根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝 光度的目标值；
    将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。
  6. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    对所述灰度图像进行均衡化处理；
    从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息；
    根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述终端中摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
  7. 根据权利要求6所述的方法，其特征在于，所述对所述灰度图像进行均衡化处理，包括：
    根据各灰度级的分布概率，确定所述灰度图像的累计概率直方图；
    根据所述累计概率直方图，按照预设规则调整所述灰度图像中各灰度级区间的累计概率；
    按照调整后各灰度级区间的累计概率，对所述灰度图像中各灰度级区间对应各像素点的灰度值进行调整，以增强所述灰度图像的对比度。
  8. 一种终端，其特征在于，包括：
    第一检测单元，用于检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；
    转化单元，用于如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为灰度图像；
    确定单元，用于根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；
    第一调整单元，用于根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
  9. 根据权利要求8所述的终端，其特征在于，所述第一检测单元检测终端的摄像装置采集到的预览图像中是否存在拍摄对象时，具体用于：
    对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度；
    如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
  10. 根据权利要求8所述的终端，其特征在于，所述确定单元403根据所述灰度图像中各像素点的灰度级，确定各灰度级的分布概率和各灰度级区间时，具体用于：
    获取所述灰度图像中各像素点的灰度值；
    根据各像素点的灰度值，确定各像素点的各灰度级；
    根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率；
    按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。
  11. 根据权利要求8所述的终端，其特征在于，所述终端还包括：第二检测单元，所述第二检测单元在所述根据各灰度级区间的累计概率调整所述灰度图像的曝光度之前，用于：
    检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间；
    如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度。
  12. 根据权利要求11所述的终端，其特征在于，所述第一调整单元根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度时，具体用于：
    根据预设的累计概率与曝光度的对应关系，确定各灰度级区间中大于预设阈值的累计概率对应的曝光度的目标值；
    将所述灰度图像中所述累计概率大于预设阈值的灰度级区间的曝光度调整至所述目标值。
  13. 根据权利要求8所述的终端，其特征在于，所述终端还包括第二调整单元，所述第二调整单元，用于：
    对所述灰度图像进行均衡化处理；
    从均衡化处理后的灰度图像中确定出所述拍摄对象的位置信息；
    根据所述拍摄对象在均衡化处理后的灰度图像中的位置信息，调整所述终端中摄像装置的焦距，并采用调整后的曝光度和焦距进行图像拍摄。
  14. 根据权利要求13所述的终端，其特征在于，所述第二调整单元对所述灰度图像进行均衡化处理时，具体用于：
    根据各灰度级的分布概率，确定所述灰度图像的累计概率直方图；
    根据所述累计概率直方图，按照预设规则调整所述灰度图像中各灰度级区间的累计概率；
    按照调整后各灰度级区间的累计概率，对所述灰度图像中各灰度级区间对应各像素点的灰度值进行调整，以增强所述灰度图像的对比度。
  15. 一种终端，其特征在于，包括处理器、输入设备、输出设备和存储器，所述处理器、输入设备、输出设备和存储器相互连接，其中，所述存储器用于存储计算机程序，所述计算机程序包括程序指令，所述处理器被配置用于调用所述程序指令，用于执行：
    检测终端的摄像装置采集到的预览图像中是否存在拍摄对象；
    如果检测到所述终端的摄像装置采集到的预览图像中不存在拍摄对象，则将所述预览图像转化为 灰度图像；
    根据所述灰度图像中各像素点的灰度级，确定各像素点的灰度级的分布概率和所述灰度图像的各灰度级区间；
    根据各灰度级区间的累计概率调整所述灰度图像的曝光度，并按照调整后的曝光度进行图像拍摄，其中，所述累计概率是灰度级区间内的灰度级的分布概率之和。
  16. 根据权利要求15所述的终端，其特征在于，所述处理器检测终端的摄像装置采集到的预览图像中是否存在拍摄对象时，具体用于：
    对获取到的所述终端的摄像装置采集到的预览图像进行图像处理，得到所述预览图像的模糊度；
    如果检测到所述预览图像的模糊度大于预设的模糊度阈值，则确定所述终端的摄像装置采集到的该所述预览图像中不存在拍摄对象。
  17. 根据权利要求15所述的终端，其特征在于，所述处理器根据所述灰度图像中各像素点的灰度级，确定各灰度级的分布概率和各灰度级区间时，具体用于：
    获取所述灰度图像中各像素点的灰度值；
    根据各像素点的灰度值，确定各像素点的各灰度级；
    根据所述灰度图像中像素点的总数量和各灰度级对应的像素点数量，确定各灰度级的分布概率；
    按照预设的划分规则对各灰度级进行区间划分，得到一个或多个灰度级区间。
  18. 根据权利要求15所述的终端，其特征在于，所述处理器在所述根据各灰度级区间的累计概率调整所述灰度图像的曝光度之前，用于：
    检测各灰度级区间中是否存在累计概率大于预设阈值的灰度级区间；
    如果检测到各灰度级区间中存在所述累计概率大于预设阈值的灰度级区间，则执行根据所述各灰度级区间的累计概率调整各灰度区间的灰度图像的曝光度。
  19. 根据权利要求15所述的终端，其特征在于，所述处理器用于执行权利要求5-7任一项所述的方法。
  20. 一种计算机可读存储介质，其特征在于，所述计算机存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令当被处理器执行时使所述处理器执行如权利要求1-7任一项所述的方法。
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