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WO2019085705A1 - 高动态范围图像曝光补偿值获取方法和装置 - Google Patents

高动态范围图像曝光补偿值获取方法和装置 Download PDF

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Publication number
WO2019085705A1
WO2019085705A1 PCT/CN2018/108639 CN2018108639W WO2019085705A1 WO 2019085705 A1 WO2019085705 A1 WO 2019085705A1 CN 2018108639 W CN2018108639 W CN 2018108639W WO 2019085705 A1 WO2019085705 A1 WO 2019085705A1
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WO
WIPO (PCT)
Prior art keywords
exposure
current scene
compensation value
image
brightness
Prior art date
Application number
PCT/CN2018/108639
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English (en)
French (fr)
Inventor
刘凯
Original Assignee
Oppo广东移动通信有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Oppo广东移动通信有限公司 filed Critical Oppo广东移动通信有限公司
Priority to EP18872022.1A priority Critical patent/EP3694203B1/en
Publication of WO2019085705A1 publication Critical patent/WO2019085705A1/zh
Priority to US16/828,920 priority patent/US11375128B2/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/71—Circuitry for evaluating the brightness variation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/40—Image enhancement or restoration using histogram techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
    • 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
    • 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
    • H04N23/743—Bracketing, i.e. taking a series of images with varying exposure conditions
    • 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
    • H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/86—Camera processing pipelines; Components thereof for processing colour signals for controlling the colour saturation of colour signals, e.g. automatic chroma control circuits
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/77—Circuits for processing the brightness signal and the chrominance signal relative to each other, e.g. adjusting the phase of the brightness signal relative to the colour signal, correcting differential gain or differential phase
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G06T2207/20208—High dynamic range [HDR] image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G06T2207/20221—Image fusion; Image merging
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths

Definitions

  • the present application relates to the field of exposure processing technologies, and in particular, to a method and apparatus for acquiring a high dynamic range image exposure compensation value.
  • HDR High-Dynamic Range
  • the terminal device when the user uses the camera to take a high dynamic range image, the terminal device usually first takes a normal exposure image of the shooting area by using an Auto Exposure Control (AEC), and then according to the advance The under- and over-exposure images are set to capture under- and over-exposed images of the same area. The captured normal exposure image, underexposed image and overexposed image are then combined by image fusion technology to obtain a high dynamic range image.
  • AEC Auto Exposure Control
  • the first object of the present application is to provide a high dynamic range image exposure compensation value acquisition method, which can adaptively determine the exposure compensation amount of the captured image according to different shooting scenes, so as to achieve the captured image. Dynamic optimal exposure compensation, which makes the quality of the captured image better and enhances the user experience.
  • a second object of the present application is to provide a high dynamic range image exposure compensation value acquisition device.
  • a third object of the present application is to propose a terminal device.
  • a fourth object of the present application is to propose a computer readable storage medium.
  • a fifth object of the present application is to propose a computer program.
  • the high dynamic range image exposure compensation value acquisition method of the first aspect of the present application includes: determining respective color channel histograms corresponding to the current scene, wherein each color channel histogram includes different brightness under each color channel. Corresponding relationship with the pixel ratio; determining the underexposure degree and the overexposure degree of the current scene according to a preset normal exposure brightness threshold, a pixel ratio threshold, and a correspondence between different brightness and pixel ratios in the respective color channels The under-exposure compensation value and the over-exposure compensation value of the current scene are determined according to the under-exposure degree and the over-exposure degree of the current scene.
  • the high dynamic range image exposure compensation value obtaining apparatus of the second aspect of the present application includes: a first determining module, configured to determine respective color channel histograms corresponding to the current scene, wherein each color channel histogram includes Corresponding relationship between different brightness and pixel ratio under each color channel; a second determining module, configured to correspond to a preset normal exposure brightness threshold, a pixel ratio threshold, and a different brightness and pixel ratio under each color channel And determining an under-exposure degree and an over-exposure degree of the current scene; and a third determining module, configured to determine an under-exposure compensation value and an over-exposure compensation value of the current scene according to the under-exposure degree and the over-exposure degree of the current scene.
  • the terminal device of the third aspect of the present application includes: a memory, a processor, and a camera module; the camera module is configured to collect an image in a current scene; and the memory is configured to be stored.
  • Executing program code the processor, configured to read executable program code stored in the memory to execute a program corresponding to the executable program code, to implement the high dynamics described in the first aspect embodiment Range image exposure compensation value acquisition method.
  • a computer readable storage medium according to an embodiment of the fourth aspect of the present invention has stored thereon a computer program, and when the computer program is executed by the processor, implements high dynamic range image exposure compensation according to the first aspect of the present invention. Value acquisition method.
  • the computer program of the embodiment of the fifth aspect of the present invention when the computer program is executed by the processor, implements the high dynamic range image exposure compensation value acquisition method described in the first aspect.
  • the technical solution disclosed in the present application has the following beneficial effects:
  • FIG. 1 is a flowchart of a method for acquiring a high dynamic range image exposure compensation value according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of a red channel histogram in accordance with an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a green channel histogram according to an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a blue channel histogram according to an embodiment of the present application.
  • FIG. 5 is a flowchart of a method for acquiring a high dynamic range image exposure compensation value according to another embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of a high dynamic range image exposure compensation value acquiring apparatus according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
  • the high dynamic range image exposure compensation value obtaining method determines the respective color channel histograms corresponding to the current scene, and according to preset normal exposure brightness threshold values, pixel ratio threshold values, and different brightness and pixels under each color channel.
  • the corresponding relationship of the ratio determines the under-exposure degree and the over-exposure degree of the current scene, and then determines the under-exposure compensation value and the over-exposure compensation value of the current scene according to the determined under-exposure degree and over-exposure degree of the current scene. Therefore, when exposure compensation is performed on the captured image, it is possible to adaptively determine the exposure compensation amount of the captured image according to different shooting scenes, so as to achieve dynamic optimal exposure compensation for the captured image, thereby enabling the captured image to be captured. Clearer display of the details on the image, more realistic reflection of the real visual effects of the current scene, improve the quality of the image, and enhance the user experience.
  • FIG. 1 is a flow chart of a method for acquiring a high dynamic range image exposure compensation value according to an embodiment of the present application.
  • the high dynamic range image exposure compensation value acquisition method of the present application may include the following steps:
  • Step 101 Determine respective color channel histograms corresponding to the current scene, where each color channel histogram includes a corresponding relationship between different brightness and pixel ratios under each color channel.
  • the high dynamic range image exposure compensation acquisition method provided by the embodiment of the present application may be performed by the high dynamic range image exposure compensation acquisition device provided by the application, where the device is configured in the terminal device to implement exposure compensation for the captured image. Take control.
  • the terminal device in this embodiment may be any hardware device having a camera function, such as a smart phone, a camera, a personal computer (PC), etc., which is not specifically limited in this application.
  • a camera function such as a smart phone, a camera, a personal computer (PC), etc.
  • the embodiment may first obtain original image data from an image sensor.
  • the original image data obtained may be the RGB data of the Beyer array, or may be other types of attributes, such as the YUV format, the YCbCr format, etc., which is not specifically limited herein.
  • RGB data In practical applications, color channel histograms are usually acquired using RGB data. Therefore, in this embodiment, if the acquired original image data is not RGB data, it is necessary to first convert the non-RGB data into RGB data.
  • the histogram of each color channel corresponding to the current scene is determined, which is not described in detail in this embodiment.
  • the RGB data acquired in this embodiment includes red (R), green (G), and blue (B) three color channels
  • the corresponding determined color channel histograms are three, respectively. It is a red channel histogram, a green channel histogram, and a blue channel histogram.
  • FIG. 2 is a red channel histogram
  • FIG. 3 is a green channel histogram
  • FIG. 4 is a blue channel histogram.
  • the x-axis represents the image brightness
  • the y-axis represents the proportion of pixels in the image where the pixels are located under the brightness.
  • the corresponding determined color channel histogram is four, which are a red channel histogram and a green (Gr) channel histogram. , green (Gb) channel histogram and blue channel histogram.
  • Step 102 Determine a degree of underexposure and an overexposure of the current scene according to a preset normal exposure brightness threshold, a pixel ratio threshold, and a correspondence between different brightness and pixel ratios under each color channel.
  • the response of the image sensor is close to a linear relationship in practical applications, for the image we want to render, if it is not corrected, it is directly displayed on the display screen, even according to the preset normal exposure.
  • the image whose brightness threshold is brightness-adjusted is not exposed, and it is also possible that over-exposure occurs in the image presented on the display screen. Therefore, in order to correctly output a response image conforming to the human eye's brightness on various devices, a corresponding correction operation is required, and the function of the correction is a gamma curve.
  • the embodiment may determine a normal exposure brightness threshold according to a gamma curve corresponding to the camera.
  • the determined normal exposure brightness threshold, the pixel ratio threshold, and the corresponding relationship between the different brightness and the pixel ratio under each color channel are used to determine the under-exposure degree and the over-exposure degree of the current scene.
  • the pixel ratio of each color channel may be started from 0 according to the histogram of each color channel, and then the superimposition operation is performed according to the manner of increasing the brightness until the pixel The superposition of the scale and the value reach the pixel ratio threshold, and then determine the superposition of the pixel ratio and the value of the brightness value corresponding to the pixel ratio threshold position.
  • the brightness value may be compared with the normal exposure brightness threshold to obtain the underexposure level of the current scene.
  • the degree of underexposure and the degree of overexposure may be a specific value or a range of values, and the application does not specifically limit this.
  • Step 103 Determine an under-exposure compensation value and an over-exposure compensation value of the current scene according to the under-exposure degree and the over-exposure degree of the current scene.
  • the under-exposure degree of the current scene and the normal exposure brightness threshold may be separately processed to obtain a corresponding difference, and then the under-exposure compensation value of the current scene is determined according to the difference.
  • the over-exposure degree of the current scene is also compared with the normal exposure brightness threshold to obtain a corresponding difference, and then the over-exposure compensation value of the current scene is determined according to the difference.
  • Step 104 Acquire a high dynamic range image corresponding to the current scene according to the underexposure compensation value and the overexposure compensation value.
  • the embodiment may respectively obtain the current scene according to the underexposure compensation value and the overexposure compensation value.
  • Exposure image and underexposed image The acquired normal exposure image, underexposed image and overexposed image are then image-fused to obtain a high-quality high dynamic range image capable of displaying more image details.
  • an overexposed image of the current scene may be acquired based on the underexposure compensation value; an underexposed image of the current scene is acquired based on the overexposure compensation value; a normal exposure image of the current scene is acquired; an underexposed image, an overexposed image, and Normal exposure image fusion processing generates a high dynamic range image corresponding to the current scene.
  • the high dynamic range image exposure compensation value obtaining device of the present application determines a histogram of each color channel of the normal exposure image based on the normal exposure image of the current scene captured by the imaging sensor, and then according to each color channel histogram and normal exposure.
  • Brightness threshold and pixel ratio threshold adaptively determine the underexposure brightness compensation value and the overexposure brightness compensation value, so that the high dynamic range image obtained after image fusion of the underexposed image, overexposed image and normal exposure image can be sharper
  • the details on the displayed image more realistically reflect the true visual effect of the current scene and improve the quality of the image.
  • the histogram of each color channel corresponding to the current scene is determined, and according to a preset normal exposure brightness threshold, a pixel ratio threshold, and different brightness under each color channel. Corresponding relationship with the pixel ratio determines the under-exposure degree and over-exposure degree of the current scene, and then determines the under-exposure compensation value and the over-exposure compensation value of the current scene according to the under-exposure degree and the over-exposure degree of the current scene.
  • the under-exposure compensation value and the over-exposure compensation of the current scene are determined by determining the under-exposure degree and the over-exposure degree of the current scene, and based on the difference between the normal exposure brightness threshold and the under-exposure level and the over-exposure level. value.
  • the high dynamic range image exposure compensation value acquisition method of the present application will be further described below with reference to FIG. 3 as an example to determine the process of the underexposure compensation value.
  • FIG. 3 is a flow chart of another high dynamic range image exposure compensation value acquisition method in accordance with the present application.
  • the high dynamic range image exposure compensation value acquisition method of the present application may include the following steps:
  • Step 301 Determine a histogram of each color channel corresponding to the current scene, where each color channel histogram includes a correspondence between different brightness and pixel ratio under each color channel.
  • Step 302 According to a preset first exposure brightness threshold, a first pixel ratio threshold, and different brightness and pixel ratios under each color channel, the pixel ratio values in each color channel histogram are counted according to the order of brightness from low to high. with.
  • the magnitude of the first exposure brightness threshold may be determined according to the non-underexposure minimum brightness value of the image sensor; correspondingly, the size of the second exposure brightness threshold for determining the degree of overexposure of each color channel may be according to the image sensor The minimum brightness value for non-overexposure is determined.
  • Step 303 When the sum of the pixel ratio values of the color channels reaches the first pixel ratio threshold, determine respective first brightness values corresponding to the respective color channels.
  • Step 304 Determine a degree of underexposure of the current scene according to a minimum value of each of the first brightness values and a first brightness difference value of the first exposure brightness threshold.
  • the present application determines the underexposure degree of the current scene by selecting the minimum value of the first brightness value in each color channel histogram, thereby ensuring a more comprehensive exposure of the current scene image. Compensation makes the acquired image quality better.
  • the red channel histogram is a red channel histogram, a green channel histogram, and a blue channel histogram
  • the red channel can be respectively used.
  • the histogram, the green channel histogram, and the blue channel histogram are incremented in a direction from 0 to a luminance value of 255, and the corresponding pixels in the red channel histogram, the green channel histogram, and the blue channel histogram are superimposed respectively.
  • the scale value until the sum of the pixel scale values in the red channel histogram, the green channel histogram, and the blue channel histogram reaches the first pixel ratio threshold of 8%. Then, the sum of the pixel ratio values in the red channel histogram, the green channel histogram, and the blue channel histogram is 8%, and the corresponding first luminance values are 3 lux, 4 lux, respectively. 6lux.
  • the first luminance value of the red channel histogram is the minimum value and is different from the first exposure luminance threshold 10 by 7 luminance values, so the first luminance value of the red channel histogram can be obtained.
  • the seven brightness values between the first exposure brightness threshold and the first exposure brightness threshold are determined as the under-exposure level of the current scene.
  • Step 305 Determine, according to a relationship between the preset difference value and the exposure compensation value, a corresponding under-exposure compensation value corresponding to the first brightness difference value.
  • the relationship between the preset difference and the exposure compensation value may be preset according to different shooting scenes, which is not specifically limited in this application.
  • the query may be performed in the relationship between the difference and the exposure compensation value according to the degree of under-exposure to determine the under-exposure compensation corresponding to the first luminance difference. value.
  • the current scene is determined by the correspondence between the first exposure brightness threshold, the first pixel ratio threshold, and the different brightness and pixel ratios under each color channel.
  • the degree of underexposure is then determined according to the degree of underexposure in the relationship between the pre-established difference and the exposure compensation value, and the corresponding underexposure compensation value is determined. Therefore, when exposure compensation is performed on the captured image, it is possible to adaptively determine the exposure compensation amount of the captured image according to different shooting scenes, so as to achieve dynamic optimal exposure compensation for the captured image, thereby enabling the captured image to be more Clearly display the details on the image, more realistically reflect the real visual effect of the current scene, improve the quality of the image, and enhance the user experience.
  • the present application also proposes a high dynamic range image exposure compensation value acquisition device.
  • FIG. 4 is a schematic structural diagram of a high dynamic range image exposure compensation value acquiring apparatus according to an embodiment of the present application.
  • the high dynamic range image exposure compensation value obtaining apparatus of the present application includes: a first determining module 11, a second determining module 12, and a third determining module 13.
  • the first determining module 11 is configured to determine respective color channel histograms corresponding to the current scene, where each color channel histogram includes a corresponding relationship between different brightness and pixel ratios under each color channel;
  • the second determining module 12 is configured to determine an under-exposure degree and an over-exposure degree of the current scene according to a preset normal exposure brightness threshold, a pixel ratio threshold, and a correspondence between different brightness and pixel ratios in the color channels. ;
  • the third determining module 13 is configured to determine an underexposure compensation value and an overexposure compensation value of the current scene according to the underexposure level and the overexposure degree of the current scene.
  • the normal exposure brightness threshold preset in the present application includes: a first exposure brightness threshold; a pixel ratio threshold, including a first pixel ratio threshold.
  • the second determining module 12 of the present application includes:
  • a statistical unit configured to count a sum of pixel scale values in the histograms of the color channels according to a sequence of brightness from low to high;
  • a first determining unit configured to determine, when the sum of the pixel ratio values of the color channels reaches a first pixel ratio threshold, each first brightness value corresponding to each color channel;
  • a second determining unit configured to determine an underexposure degree of the current scene according to a minimum value of the first brightness values and a first brightness difference value of the first exposure brightness threshold.
  • the third determining module is specifically configured to:
  • the embodiment of the present application further includes: an acquiring module.
  • the acquiring module is configured to acquire a high dynamic range image corresponding to the current scene according to the underexposure compensation value and the overexposure compensation value.
  • the acquiring module includes:
  • a first acquiring subunit configured to acquire an overexposed image of the current scene based on the underexposure compensation value
  • a second acquiring subunit configured to acquire an underexposed image of the current scene based on the overexposure compensation value
  • a third acquiring subunit configured to acquire a normal exposure image of the current scene
  • the embodiment of the present application further includes: a fourth determining module.
  • the fourth determining module is configured to determine the normal exposure brightness threshold according to a gamma curve corresponding to the imaging device.
  • the apparatus for obtaining a high dynamic range image exposure compensation value determines a histogram of each color channel corresponding to the current scene, and according to a preset normal exposure brightness threshold, a pixel ratio threshold, and a different color channel. The correspondence between the brightness and the pixel ratio determines the under-exposure degree and the over-exposure degree of the current scene, and then determines the under-exposure compensation value and the over-exposure compensation value of the current scene according to the under-exposure degree and the over-exposure degree of the current scene.
  • the present application also proposes a terminal device.
  • FIG. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
  • the terminal device of the present application includes a memory 21, a processor 22, and a camera module 23;
  • the camera module 23 is configured to collect an image in a current scene
  • the memory 21 is configured to store executable program code
  • the processor 22 is configured to read the executable program code stored in the memory 21 to run a program corresponding to the executable program code for implementing the high dynamic range image exposure described in the first aspect embodiment.
  • Compensation value acquisition method comprises: determining a histogram of each color channel corresponding to the current scene, wherein each color channel histogram includes a correspondence between different brightness and pixel ratio under each color channel; according to a preset normal exposure a brightness threshold, a pixel ratio threshold, and a corresponding relationship between different brightness and pixel ratios in the respective color channels, determining an under-exposure level and an over-exposure level of the current scene; and an under-exposure level and an over-exposure according to the current scene Degree, determine the under-exposure compensation value and over-exposure compensation value of the current scene.
  • the terminal device in this embodiment may be any hardware device having a camera function, such as a smart phone, a camera, a personal computer (PC), etc., which is not specifically limited in this application.
  • a camera function such as a smart phone, a camera, a personal computer (PC), etc.
  • the terminal device by determining a histogram of each color channel corresponding to the current scene, and according to a preset normal exposure brightness threshold, a pixel ratio threshold, and a corresponding relationship between different brightness and pixel ratios in each color channel, Determine the under-exposure degree and over-exposure degree of the current scene, and then determine the under-exposure compensation value and the over-exposure compensation value of the current scene according to the under-exposure degree and the over-exposure degree of the current scene.
  • the present application also proposes a computer readable storage medium.
  • the computer readable storage medium having stored thereon a computer program that, when executed by the processor, implements the high dynamic range image exposure compensation value acquisition method of the first aspect of the embodiment.
  • the method for obtaining a high dynamic range image exposure compensation value comprises: determining a histogram of each color channel corresponding to the current scene, wherein each color channel histogram includes a correspondence between different brightness and pixel ratio under each color channel; according to a preset normal exposure a brightness threshold, a pixel ratio threshold, and a corresponding relationship between different brightness and pixel ratios in the respective color channels, determining an under-exposure level and an over-exposure level of the current scene; and an under-exposure level and an over-exposure according to the current scene Degree, determine the under-exposure compensation value and over-exposure compensation value of the current scene.
  • the present application also proposes a computer program.
  • the high dynamic range image exposure compensation value acquisition method described in the first aspect embodiment is implemented.
  • the terms "set”, “connected” and the like shall be understood broadly, and may be either mechanical or electrical, as may be directly connected or passed through, unless otherwise specifically defined and defined.
  • the intermediate medium is indirectly connected, and may be an internal connection of two elements or an interaction of two elements unless explicitly defined otherwise.
  • the specific meanings of the above terms in the present application can be understood on a case-by-case basis.
  • first and second are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated.
  • features defining “first” or “second” may include at least one of the features, either explicitly or implicitly.
  • portions of the application can be implemented in hardware, software, firmware, or a combination thereof.
  • multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.
  • the above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like. While the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are illustrative and are not to be construed as limiting the scope of the present application. The embodiments are subject to variations, modifications, substitutions and variations.

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Abstract

本申请公开了一种高动态范围图像曝光补偿值获取方法和装置，其中方法，包括：确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定当前场景的欠曝光程度及过曝光程度；根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。本申请的方法能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄图像的动态最优曝光补偿，从而使得拍摄图像的质量佳，提升了用户体验。

Description

高动态范围图像曝光补偿值获取方法和装置
相关申请的交叉引用
本申请要求OPPO广东移动通信有限公司于2017年10月30日提交的、申请名称为“高动态范围图像曝光补偿值获取方法和装置”的、中国专利申请号“201711051871.6”的优先权。
技术领域
本申请涉及曝光处理技术领域，尤其涉及一种高动态范围图像曝光补偿值获取方法和装置。
背景技术
现如今，各种终端设备已成为用户日常生活的必备品，用户可通过终端设备进行多种功能的操作。例如，利用终端设备中的相机拍摄高动态范围图像(High-Dynamic Range，简称HDR)。其中，HDR是通过将正常曝光图像、欠曝光图像和过曝光图像三个图像进行融合得到的。
在实际应用过程中，用户利用相机拍摄高动态范围图像时，终端设备通常是先利用自动曝光控制系统(Auto Exposure Control，简称为：AEC)对拍摄区域拍摄一张正常曝光图像，再分别根据预先设置的欠曝光量和过曝光量拍摄相同区域的欠曝光图像和过曝光图像。然后经过图像融合技术将拍摄的正常曝光图像、欠曝光图像及过曝光图像进行合成，以得到高动态范围图像。
然而，由于实际拍摄的环境存在较大差别，因此通过上述方式拍摄高动态范围图像时，或多或少会导致拍摄图像出现过曝，或者欠曝的情况，使得最终拍摄的画面质量及效果较差。
发明内容
本申请旨在至少在一定程度上解决上述的技术缺陷之一。
为此，本申请的第一个目的在于提出一种高动态范围图像曝光补偿值获取方法，该方法能够根据不同的拍摄场景自适应的确定出拍摄图像的曝光补偿量，以实现对拍摄图像的动态最优曝光补偿，从而使得拍摄图像的质量佳，提升了用户体验。
本申请的第二个目的在于提出一种高动态范围图像曝光补偿值获取装置。
本申请的第三个目的在于提出一种终端设备。
本申请的第四个目的在于提出一种计算机可读存储介质。
本申请的第五个目的在于提出一种计算机程序。
为了实现上述目的，本申请第一方面实施例的高动态范围图像曝光补偿值获取方法，包括：确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
为了实现上述目的，本申请第二方面实施例的高动态范围图像曝光补偿值获取装置，包括：第一确定模块，用于确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；第二确定模块，用于根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；第三确定模块，用于根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
为了实现上述目的，本申请第三方面实施例的终端设备，包括：存储器、处理器及摄像模组；所述摄像模组，用于采集当前场景下的图像；所述存储器，用于存储可执行程序代码；所述处理器，用于读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于实现第一方面实施例所述的高动态范围图像曝光补偿值获取方法。
为了实现上述目的，本申请第四方面实施例的计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时，实现第一方面实施例所述的高动态范围图像曝光补偿值获取方法。
为了实现上述目的，本申请第五方面实施例的计算机程序，当所述计算机程序被处理器执行时，以实现第一方面实施例所述的高动态范围图像曝光补偿值获取方法。本申请公开的技术方案，具有如下有益效果：
通过确定当前场景对应的各颜色通道直方图，并根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定出当前场景的欠曝光程度及过曝光程度，然后根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值和过曝光补偿值。由此，实现了在对拍摄画面进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄画面的动态最优曝光补偿，从而使得拍摄画面的能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
本申请附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本申请的实践了解到。
附图说明
本申请上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显 和容易理解，其中，
图1是根据本申请一个实施例的高动态范围图像曝光补偿值获取方法的流程图；
图2是根据本申请一个实施例的红色通道直方图的示意图；
图3是根据本申请一个实施例的绿色通道直方图的示意图；
图4是根据本申请一个实施例的蓝色通道直方图的示意图；
图5是根据本申请另一个实施例的高动态范围图像曝光补偿值获取方法的流程图；
图6是根据本申请一个实施例的高动态范围图像曝光补偿值获取装置的结构示意图；
图7是根据本申请一个实施例的终端设备的结构示意图。
具体实施方式
下面详细描述本申请的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本申请，而不能理解为对本申请的限制。
为了解决相关技术中，利用各种终端设备的相机拍摄高动态范围图像时，存在的拍摄图像出现过曝或者欠曝的情况，进而导致最终拍摄图像的质量及效果较差的问题，提出了一种高动态范围图像曝光补偿值获取方法。
本申请提供的高动态范围图像曝光补偿值获取方法，通过确定当前场景对应的各颜色通道直方图，并根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定出当前场景的欠曝光程度及过曝光程度，然后根据确定的当前场景的欠曝光程度及过曝光程度，确定出当前场景的欠曝光补偿值及过曝光补偿值。由此，实现了在对拍摄图像进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像的曝光补偿量，以实现对拍摄图像的动态最优曝光补偿，从而使得拍摄图像的能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
下面参考附图描述本申请实施例的高动态范围图像曝光补偿值获取方法。
图1是根据本申请一个实施例的高动态范围图像曝光补偿值获取方法的流程图。
如图1所示，本申请的高动态范围图像曝光补偿值获取方法可以包括以下步骤：
步骤101，确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系。
可选的，本申请实施例提供的高动态范围图像曝光补偿获取方法，可以由本申请提供的高动态范围图像曝光补偿获取装置执行，上述装置配置于终端设备中，以实现对拍摄图像的曝光补偿进行控制。
其中，本实施例中终端设备可以是任意具有拍照功能的硬件设备，比如智能手机、照相机、个人计算机(personal computer，简称为PC)等等，本申请对此不作具体限定。
作为本申请的一种可选的实现方式，本实施例可先从影像传感器中获取原始图像数据。 其中，获取的原始图像数据可以是Beyer阵列的RGB数据，或者，也可能是其他类型属性，比如YUV格式，YCbCr格式等，本申请在此不对其作具体限定。
在实际应用中，颜色通道直方图通常是利用RGB数据进行获取。因此本实施例中，若获取的原始图像数据不是RGB数据，则需要先将非RGB数据转为RGB数据。
然后，再根据RGB数据，确定出当前场景对应的各颜色通道直方图，本实施例对此不作过多赘述。
需要说明的是，若本实施例中获取的RGB数据中包括红(R)、绿(G)、蓝(B)三个颜色通道，那么对应确定的各颜色通道直方图则为三个，分别为红色通道直方图、绿色通道直方图以及蓝色通道直方图。
进一步的，上述确定的三种颜色通道直方图，可具体可参见图2-图4所示，图2为红色通道直方图，图3为绿色通道直方图，图4为蓝色通道直方图。其中，各颜色通道直方图中，x轴表示图像亮度，y轴表示图像中各像素位于该亮度下的像素比例。
若本实施例中获取的RGB数据包括R，Gr，Gb，B四个颜色通道时，那么对应确定的颜色通道直方图则为四个，分别为红色通道直方图、绿色(Gr)通道直方图、绿色(Gb)通道直方图以及蓝色通道直方图。
步骤102，根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定当前场景的欠曝光程度及过曝光程度。
可选的，由于在实际应用中，图像传感器的响应是接近线性关系的，对于我们所要渲染的图像来讲，如果不进行校正，而是直接显示在显示屏幕上，即使根据预设的正常曝光亮度阈值进行亮度调节的图像不过曝，也有可能在显示屏幕上呈现出的图像中出现过曝。因此，为了能在各种设备上正确输出符合人眼对亮度的响应图像，就需要进行相应的校正操作，该校正的函数即为伽马曲线。
因此，在实现步骤102步骤之前，本实施例可根据摄像装置对应的伽马曲线，确定正常曝光亮度阈值。
然后，再利用确定的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定当前场景的欠曝光程度及过曝光程度。
作为一种可选的实现方式，确定当前场景的欠曝光程度时，可根据各颜色通道直方图，将各颜色通道的像素比例从0开始，然后按照亮度增加的方式，进行叠加操作，直到像素比例的叠加和值到达像素比例阈值为止，然后确定像素比例的叠加和值到达像素比例阈值位置，所对应的亮度值。
在确定出与像素比例阈值对应的亮度值之后，可将上述亮度值与正常曝光亮度阈值进行比对，以得到当前场景的欠曝光程度。
同样的，确定当前场景的过曝光程度时，与确定当前场景的欠曝光程度的过程相似，唯一的区别点在于，需要将各颜色通道中的像素比例按照亮度从高到低递减的方式进行叠加。
其中，欠曝光程度和过曝光程度可以为一个具体数值，也可以为一个数值范围，本申 请对此不作具体限定。
步骤103，根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
作为一种可选的实现方式，可分别将当前场景的欠曝光程度与正常曝光亮度阈值进行作差处理，以得到对应的差值，然后根据上述差值确定当前场景的欠曝光补偿值。
同时，也将当前场景的过曝光程度与正常曝光亮度阈值进行作差处理，以得到对应的差值，然后根据差值确定当前场景的过曝光补偿值。
步骤104，根据欠曝光补偿值及过曝光补偿值，获取当前场景对应的高动态范围图像。
可选的，当高动态范围图像曝光补偿值获取装置确定出当前图像欠曝光补偿值及过曝光补偿值之后，本实施例可根据上述欠曝光补偿值和过曝光补偿值分别获取当前场景的过曝光图像及欠曝光图像。然后将获取的正常曝光图像、欠曝光图像及过曝光图像进行图像融合，得到一张能够显示更多图像细节的高质量高动态范围图像。
具体实现时，可基于欠曝光补偿值，获取当前场景的过曝光图像；基于过曝光补偿值，获取当前场景的欠曝光图像；获取当前场景的正常曝光图像；将欠曝光图像、过曝光图像及正常曝光图像融合处理，生成当前场景对应的高动态范围图像。
可以理解的是，本申请高动态范围图像曝光补偿值获取装置，基于摄像传感器拍摄的当前场景的正常曝光图像，确定正常曝光图像各颜色通道的直方图，然后根据各颜色通道直方图、正常曝光亮度阈值及像素比例阈值适应性的确定欠曝光亮度补偿值及过曝光亮度补偿值，使得拍摄的欠曝光图像、过曝光图像及正常曝光图像进行图像融合之后得到的高动态范围图像，能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量。
本申请实施例的高动态范围图像曝光补偿值获取方法中，通过确定当前场景对应的各颜色通道直方图，并根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定出当前场景的欠曝光程度及过曝光程度，然后根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值和过曝光补偿值。由此，实现了在对拍摄画面进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄画面的动态最优曝光补偿，从而使得拍摄画面的能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
通过上述分析可知，通过确定当前场景的欠曝光程度及过曝光程度，并基于正常曝光亮度阈值与欠曝光程度和过曝光程度之间的差值，确定当前场景的欠曝光补偿值及过曝光补偿值。下面结合图3，以确定欠曝光补偿值的过程为例，对本申请的高动态范围图像曝光补偿值获取方法进行进一步的描述。
图3是根据本申请的另一个高动态范围图像曝光补偿值获取方法的流程图。
如图3所示，本申请的高动态范围图像曝光补偿值获取方法可以包括以下步骤：
步骤301，确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系。
步骤302，根据预设的第一曝光亮度阈值、第一像素比例阈值、及各颜色通道下的不同亮度与像素比例，按照亮度由低至高的顺序，统计各颜色通道直方图中像素比例值的和。
其中，第一曝光亮度阈值的大小，可以根据图像传感器的非欠曝光最低亮度值确定；相应的，用于确定各颜色通道的过曝光程度的第二曝光亮度阈值的大小，可以根据图像传感器的非过曝光最低亮度值确定。
步骤303，当各颜色通道像素比例值的和达到第一像素比例阈值时，确定各颜色通道分别对应的各第一亮度值。
步骤304，根据各第一亮度值中的最小值，与第一曝光亮度阈值的第一亮度差值，确定当前场景的欠曝光程度。
需要说明的是，由于各颜色通道直方图的第一亮度值参差不齐，若选取的与第一曝光亮度阈值之间差值较少的第一亮度值，确定当前场景的欠曝光程度，则可能会导致后期对当前场景的图像进行曝光补偿之后，图像仍然存在欠曝光的问题。
因此，为了有效的解决上述存在的问题，本申请通过选取各颜色通道直方图中第一亮度值的最小值，确定当前场景的欠曝光程度，从而保证了对当前场景的图像进行更全面的曝光补偿，使得获取到的图像质量更好。
举例说明，若第一曝光亮度阈值为10，第一像素比例阈值为8％，且各颜色通道直方图为红色通道直方图、绿色通道直方图及蓝色通道直方图，那么可分别将红色通道直方图、绿色通道直方图及蓝色通道直方图按照由亮度值由0向亮度值为255的方向进行递增，同时分别叠加红色通道直方图、绿色通道直方图及蓝色通道直方图中对应像素比例值，直到红色通道直方图、绿色通道直方图及蓝色通道直方图中各像素比例值的和均到达第一像素比例阈值8％时为止。然后统计出红色通道直方图、绿色通道直方图及蓝色通道直方图中像素比例值的和到达第一像素比例值8％时，分别对应的第一亮度值为3勒克斯(lux)、4lux、6lux。
由上述统计的数据可以看出，红色通道直方图的第一亮度值为最小值，且与第一曝光亮度阈值10之间相差7个亮度值，因此可以将红色通道直方图的第一亮度值与第一曝光亮度阈值之间的7个亮度值确定为当前场景的欠曝光程度。
步骤305，根据预设的差值与曝光补偿值的关系，确定与第一亮度差值，对应的欠曝光补偿值。
其中，预设的差值与曝光补偿值的关系可以是根据不同拍摄场景进行预先设置的，本申请对此不作具体限定。
也就是说，在本实施例确定出当前场景的欠曝光程度之后，可根据欠曝光程度在差值与曝光补偿值的关系列表中进行查询，以确定出第一亮度差值对应的欠曝光补偿值。
本申请实施例的高动态范围图像曝光补偿值获取方法中，通过基于第一曝光亮度阈值、第一像素比例阈值及各颜色通道下的不同亮度与像素比例之间的对应关系，确定出当前场 景的欠曝光程度，然后根据欠曝光程度在预先建立的差值与曝光补偿值的关系列表中，确定对应的欠曝光补偿值。由此，实现了在对拍摄画面进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄画面的动态最优曝光补偿，从而使得拍摄画面的能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
为了实现上述实施例，本申请还提出了一种高动态范围图像曝光补偿值获取装置。
图4是根据本申请一个实施例的高动态范围图像曝光补偿值获取装置的结构示意图。
如图4所示，本申请的高动态范围图像曝光补偿值获取装置包括：第一确定模块11、第二确定模块12及第三确定模块13。
其中，第一确定模块11用于确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；
第二确定模块12用于根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；
第三确定模块13用于根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
在本申请的另一个实施例中，本申请中预设的正常曝光亮度阈值包括：第一曝光亮度阈值；像素比例阈值，包括第一像素比例阈值。
本申请第二确定模块12包括：
统计单元，用于按照亮度由低至高的顺序，统计所述各颜色通道直方图中像素比例值的和；
第一确定单元，用于当各颜色通道像素比例值的和达到第一像素比例阈值时，确定各颜色通道分别对应的各第一亮度值；
第二确定单元，用于根据所述各第一亮度值中的最小值，与所述第一曝光亮度阈值的第一亮度差值，确定所述当前场景的欠曝光程度。
在本申请的另一个实施例中，所述第三确定模块，具体用于：
根据预设的差值与曝光补偿值的关系，确定与所述第一亮度差值，对应的欠曝光补偿值。
在本申请的另一个实施例中，本申请实施例还包括：获取模块。
其中所述获取模块，用于根据所述欠曝光补偿值及过曝光补偿值，获取所述当前场景对应的高动态范围图像。
在本申请的另一个实施例中，所述获取模块，包括：
第一获取子单元，用于基于所述欠曝光补偿值，获取所述当前场景的过曝光图像；
第二获取子单元，用于基于所述过曝光补偿值，获取所述当前场景的欠曝光图像；
第三获取子单元，用于获取所述当前场景的正常曝光图像；
生成子单元，用于将所述欠曝光图像、过曝光图像及正常曝光图像融合处理，生成所 述当前场景对应的高动态范围图像。
在本申请的另一个实施例中，本申请实施例还包括：第四确定模块。
其中，第四确定模块用于根据摄像装置对应的伽马曲线，确定所述正常曝光亮度阈值。
需要说明的是，前述对高动态范围图像曝光补偿值获取方法实施例的解释说明也适用于该实施例的高动态范围图像曝光补偿值获取装置，其实现原理类似，此处不再赘述。
本申请实施例提供的高动态范围图像曝光补偿值获取装置中，通过确定当前场景对应的各颜色通道直方图，并根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定出当前场景的欠曝光程度及过曝光程度，然后根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值和过曝光补偿值。由此，实现了在对拍摄图像进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄图像的动态最优曝光补偿，从而使得拍摄画面的能够更清晰的显示图像上的细节，更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
为了实现上述实施例，本申请还提出一种终端设备。
图5是根据本申请一个实施例的终端设备的结构示意图。
参见图5，本申请终端设备包括存储器21、处理器22及摄像模组23；
所述摄像模组23用于采集当前场景下的图像；
所述存储器21用于存储可执行程序代码；
所述处理器22用于读取所述存储器21中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于实现第一方面实施例所述的高动态范围图像曝光补偿值获取方法。其中高动态范围图像曝光补偿值获取方法包括：确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
其中，本实施例中终端设备可以是任意具有拍照功能的硬件设备，比如智能手机、照相机、个人计算机(personal computer，简称为PC)等等，本申请对此不作具体限定。
需要说明的是，前述对高动态范围图像曝光补偿值获取方法实施例的解释说明也适用于该实施例的终端设备，其实现原理类似，此处不再赘述。
本申请实施例提供的终端设备中，通过确定当前场景对应的各颜色通道直方图，并根据预设的正常曝光亮度阈值、像素比例阈值、及各颜色通道下的不同亮度与像素比例的对应关系，确定出当前场景的欠曝光程度及过曝光程度，然后根据当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值和过曝光补偿值。由此，实现了在对拍摄图像进行曝光补偿时，能够根据不同的拍摄场景自适应的确定出拍摄图像曝光补偿量，以实现对拍摄图像的动态最优曝光补偿，从而使得拍摄画面的能够更清晰的显示图像上的细节， 更真实的反映当前场景的真实视觉效果，提高了图像的质量，提升了用户体验。
为了实现上述实施例，本申请还提出了一种计算机可读存储介质。
该计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现第一方面实施例的高动态范围图像曝光补偿值获取方法。其中高动态范围图像曝光补偿值获取方法包括：确定当前场景对应的各颜色通道直方图，其中各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
为了实现上述实施例，本申请还提出一种计算机程序。
其中，当计算机程序被处理器执行时，以实现第一方面实施例所述的高动态范围图像曝光补偿值获取方法。
在本申请中，除非另有明确的规定和限定，术语“设置”、“连接”等术语应做广义理解，例如，可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通或两个元件的相互作用关系，除非另有明确的限定。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请中的具体含义。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施例或示例中。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现特定逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本申请的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本申请的实施例所属技术领域的技术人员所理解。
应当理解，本申请的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中， 该程序在执行时，包括方法实施例的步骤之一或其组合。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本申请的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本申请的限制，本领域的普通技术人员在本申请的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (15)

  1. 一种高动态范围图像曝光补偿值获取方法，其特征在于，包括：
    确定当前场景对应的各颜色通道直方图，其中，各颜色通道直方图包括各颜色通道下的不同亮度与像素比例的对应关系；
    根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；
    根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
  2. 如权利要求1所述的方法，其特征在于，
    所述正常曝光亮度阈值，包括第一曝光亮度阈值；
    所述像素比例阈值，包括第一像素比例阈值；
    所述确定所述当前场景的欠曝光程度包括：
    按照亮度由低至高的顺序，统计所述各颜色通道直方图中像素比例值的和；
    当各颜色通道像素比例值的和达到第一像素比例阈值时，确定各颜色通道分别对应的各第一亮度值；
    根据所述各第一亮度值中的最小值，与所述第一曝光亮度阈值的第一亮度差值，确定所述当前场景的欠曝光程度。
  3. 如权利要求2所述的方法，其特征在于，所述确定当前场景的欠曝光补偿值，包括：
    根据预设的差值与曝光补偿值的关系，确定与所述第一亮度差值，对应的欠曝光补偿值。
  4. 如权利要求1-3任一所述的方法，其特征在于，所述确定当前场景的欠曝光补偿值及过曝光补偿值之后，还包括：
    根据所述欠曝光补偿值及过曝光补偿值，获取所述当前场景对应的高动态范围图像。
  5. 如权利要求4所述的方法，其特征在于，所述根据所述欠曝光补偿值及过曝光补偿值，获取所述当前场景对应的高动态范围图像，包括：
    基于所述欠曝光补偿值，获取所述当前场景的过曝光图像；
    基于所述过曝光补偿值，获取所述当前场景的欠曝光图像；
    获取所述当前场景的正常曝光图像；
    将所述欠曝光图像、过曝光图像及正常曝光图像融合处理，生成所述当前场景对应的高动态范围图像。
  6. 如权利要求1-3任一所述的方法，其特征在于，所述确定所述当前场景的欠曝光程度及过曝光程度之前，还包括：
    根据摄像装置对应的伽马曲线，确定所述正常曝光亮度阈值。
  7. 一种高动态范围图像曝光补偿值获取装置，其特征在于，包括：
    第一确定模块，用于确定当前场景对应的各颜色通道直方图，其中，各颜色通道直方 图包括各颜色通道下的不同亮度与像素比例的对应关系；
    第二确定模块，用于根据预设的正常曝光亮度阈值、像素比例阈值、及所述各颜色通道下的不同亮度与像素比例的对应关系，确定所述当前场景的欠曝光程度及过曝光程度；
    第三确定模块，用于根据所述当前场景的欠曝光程度及过曝光程度，确定当前场景的欠曝光补偿值及过曝光补偿值。
  8. 如权利要求7所述的装置，其特征在于，所述正常曝光亮度阈值，包括：第一曝光亮度阈值；
    所述像素比例阈值，包括第一像素比例阈值；
    所述第二确定模块包括：
    统计单元，用于按照亮度由低至高的顺序，统计所述各颜色通道直方图中像素比例值的和；
    第一确定单元，用于当各颜色通道像素比例值的和达到第一像素比例阈值时，确定各颜色通道分别对应的各第一亮度值；
    第二确定单元，用于根据所述各第一亮度值中的最小值，与所述第一曝光亮度阈值的第一亮度差值，确定所述当前场景的欠曝光程度。
  9. 如权利要求8所述的装置，其特征在于，所述第三确定模块，具体用于：
    根据预设的差值与曝光补偿值的关系，确定与所述第一亮度差值，对应的欠曝光补偿值。
  10. 如权利要求7-9任一所述的装置，其特征在于，还包括：
    获取模块，用于根据所述欠曝光补偿值及过曝光补偿值，获取所述当前场景对应的高动态范围图像。
  11. 如权利要求10所述的装置，其特征在于，所述获取模块，包括：
    第一获取子单元，用于基于所述欠曝光补偿值，获取所述当前场景的过曝光图像；
    第二获取子单元，用于基于所述过曝光补偿值，获取所述当前场景的欠曝光图像；
    第三获取子单元，用于获取所述当前场景的正常曝光图像；
    生成子单元，用于将所述欠曝光图像、过曝光图像及正常曝光图像融合处理，生成所述当前场景对应的高动态范围图像。
  12. 如权利要求7-9任一所述的方法，其特征在于，还包括：
    第四确定模块，用于根据摄像装置对应的伽马曲线，确定所述正常曝光亮度阈值。
  13. 一种终端设备，其特征在于，包括：存储器、处理器及摄像模组；
    所述摄像模组，用于采集当前场景下的图像；
    所述存储器，用于存储可执行程序代码；
    所述处理器，用于读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于实现如权利要求1-6任一所述的高动态范围图像曝光补偿值获取方法。
  14. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，该计算机程序 被处理器执行时，实现如权利要求1-6任一所述的高动态范围图像曝光补偿值获取方法。
  15. 一种计算机程序，其特征在于，当所述计算机程序被处理器执行时，以实现如权利要求1-6任一所述的高动态范围图像曝光补偿值获取方法。
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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090111065A (ko) * 2008-04-21 2009-10-26 엘지전자 주식회사 영상 합성 장치
CN102075688A (zh) * 2010-12-28 2011-05-25 青岛海信网络科技股份有限公司 单帧双曝光图像宽动态处理方法
US20140168486A1 (en) * 2012-12-18 2014-06-19 Google Inc. Determining Exposure Times Using Split Paxels
CN104301624A (zh) * 2014-10-30 2015-01-21 青岛海信移动通信技术股份有限公司 一种图像拍摄亮度控制方法及装置
CN104580925A (zh) * 2014-12-31 2015-04-29 安科智慧城市技术（中国）有限公司 一种控制图像亮度的方法、装置及摄像机
US20170064179A1 (en) * 2015-08-24 2017-03-02 Motorola Mobility Llc Method and Apparatus for Auto Exposure Value Detection for High Dynamic Range Imaging
CN106572311A (zh) * 2016-11-11 2017-04-19 努比亚技术有限公司 一种拍摄装置及其方法
CN107635102A (zh) * 2017-10-30 2018-01-26 广东欧珀移动通信有限公司 高动态范围图像曝光补偿值获取方法和装置
CN107888840A (zh) * 2017-10-30 2018-04-06 广东欧珀移动通信有限公司 高动态范围图像获取方法和装置

Family Cites Families (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3992177B2 (ja) * 2001-11-29 2007-10-17 株式会社リコー 画像処理装置、画像処理方法及びコンピュータ・プログラム
US8014602B2 (en) * 2006-03-29 2011-09-06 Seiko Epson Corporation Backlight image determining apparatus, backlight image determining method, backlight image correction apparatus, and backlight image correction method
JP4341691B2 (ja) * 2007-04-24 2009-10-07 ソニー株式会社 撮像装置、撮像方法、露光制御方法、プログラム
US8339475B2 (en) * 2008-12-19 2012-12-25 Qualcomm Incorporated High dynamic range image combining
US8582001B2 (en) * 2009-04-08 2013-11-12 Csr Technology Inc. Exposure control for high dynamic range image capture
CN101873435B (zh) 2009-04-23 2013-08-14 恩斯迈电子(深圳)有限公司 产生高动态范围图像的方法及其装置
CN102148936B (zh) * 2011-05-04 2012-10-17 展讯通信（上海）有限公司 一种高动态范围成像优化方法及装置
TWI521964B (zh) * 2012-02-13 2016-02-11 宏達國際電子股份有限公司 曝光値調整裝置、曝光値調整方法及其電腦程式產品
US9105078B2 (en) * 2012-05-31 2015-08-11 Apple Inc. Systems and methods for local tone mapping
CN103973988B (zh) * 2013-01-24 2018-02-02 华为终端（东莞）有限公司 场景识别方法及装置
EP2763396A1 (en) * 2013-01-30 2014-08-06 ST-Ericsson SA Automatic exposure bracketing
CN103826066B (zh) 2014-02-26 2017-05-03 芯原微电子(上海)有限公司 一种自动曝光调整方法及系统
CN104917973B (zh) 2014-03-11 2019-03-05 宏碁股份有限公司 动态曝光调整方法及其电子装置
JP6343200B2 (ja) * 2014-07-31 2018-06-13 キヤノン株式会社 撮像装置およびその制御方法ならびにプログラム
JP6110574B2 (ja) 2014-11-21 2017-04-05 エスゼット ディージェイアイ テクノロジー カンパニー リミテッドＳｚ Ｄｊｉ Ｔｅｃｈｎｏｌｏｇｙ Ｃｏ．，Ｌｔｄ ハイダイナミックレンジ画像化方法及びカメラ
CN105227858B (zh) * 2015-10-30 2019-03-05 维沃移动通信有限公司 一种图像处理方法及移动终端
JP6675194B2 (ja) * 2015-12-15 2020-04-01 キヤノン株式会社 撮像装置及びその制御方法、プログラム並びに記憶媒体
CN106791470B (zh) * 2016-12-28 2019-08-16 上海兴芯微电子科技有限公司 基于高动态范围摄像装置的曝光控制方法和装置
JP6720881B2 (ja) * 2017-01-19 2020-07-08 カシオ計算機株式会社 画像処理装置及び画像処理方法

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090111065A (ko) * 2008-04-21 2009-10-26 엘지전자 주식회사 영상 합성 장치
CN102075688A (zh) * 2010-12-28 2011-05-25 青岛海信网络科技股份有限公司 单帧双曝光图像宽动态处理方法
US20140168486A1 (en) * 2012-12-18 2014-06-19 Google Inc. Determining Exposure Times Using Split Paxels
CN104301624A (zh) * 2014-10-30 2015-01-21 青岛海信移动通信技术股份有限公司 一种图像拍摄亮度控制方法及装置
CN104580925A (zh) * 2014-12-31 2015-04-29 安科智慧城市技术（中国）有限公司 一种控制图像亮度的方法、装置及摄像机
US20170064179A1 (en) * 2015-08-24 2017-03-02 Motorola Mobility Llc Method and Apparatus for Auto Exposure Value Detection for High Dynamic Range Imaging
CN106572311A (zh) * 2016-11-11 2017-04-19 努比亚技术有限公司 一种拍摄装置及其方法
CN107635102A (zh) * 2017-10-30 2018-01-26 广东欧珀移动通信有限公司 高动态范围图像曝光补偿值获取方法和装置
CN107888840A (zh) * 2017-10-30 2018-04-06 广东欧珀移动通信有限公司 高动态范围图像获取方法和装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3694203A4 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112598609A (zh) * 2020-12-09 2021-04-02 普联技术有限公司 一种动态图像的处理方法及装置
CN117133252A (zh) * 2023-02-27 2023-11-28 荣耀终端有限公司 图像处理方法和电子设备

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