WO2023060762A1 - Procédé et appareil de traitement d'image, et support de stockage lisible par ordinateur - Google Patents

Procédé et appareil de traitement d'image, et support de stockage lisible par ordinateur Download PDF

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WO2023060762A1
WO2023060762A1 PCT/CN2021/139608 CN2021139608W WO2023060762A1 WO 2023060762 A1 WO2023060762 A1 WO 2023060762A1 CN 2021139608 W CN2021139608 W CN 2021139608W WO 2023060762 A1 WO2023060762 A1 WO 2023060762A1
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image
brightness
overexposed
exposure time
overexposure
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PCT/CN2021/139608
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English (en)
Chinese (zh)
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王鹏
余明火
张光宇
刘翔章
赵盖
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深圳创维－Rgb电子有限公司
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Publication of WO2023060762A1 publication Critical patent/WO2023060762A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time

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  • the present application relates to the technical field of image processing, for example, to an image processing method, device, and computer-readable storage medium.
  • the exposure time is usually adjusted when the picture is overexposed, so as to obtain an image with better display effect.
  • the problem with the existing technology is that simply adjusting the exposure time, no matter how you adjust it, can’t record the subjects with large brightness differences in the same scene well in the same frame, which is not conducive to improving the clarity of the obtained image, and affects Image recording effect.
  • the main purpose of the present application is to provide an image processing method, device, and computer-readable storage medium, aiming at solving the problem that the solution of adjusting the exposure time in the prior art cannot record objects with large brightness differences in the same scene well in the same scene. In the picture, it is not conducive to improving the clarity of the obtained image, and affects the image recording effect.
  • the first aspect of the present application provides an image processing method, wherein the above method includes:
  • a secondary exposure image is acquired based on the secondary exposure time, and a target image after overexposure correction processing is acquired based on the overexposure image and the secondary exposure image.
  • the above-mentioned acquisition of the over-exposed image, and acquisition of the portrait target area in the above-mentioned over-exposure image including:
  • the image to be processed is used as an overexposed image
  • the acquiring the image to be processed includes: acquiring the image to be processed by using a camera automatic exposure technology.
  • the acquisition of the overexposed pixels in the image to be processed based on the above overexposure brightness threshold includes:
  • the color space of the image to be processed is converted into an HSL model, and pixels whose luminance values are greater than the overexposed brightness threshold in the converted image to be processed are used as the overexposed pixels.
  • the above-mentioned overexposure brightness threshold is 0.9.
  • the aforementioned acquisition of the portrait target area in the aforementioned overexposed image includes:
  • the regions corresponding to the recognized faces are respectively used as the above-mentioned portrait target regions.
  • the above method respectively obtains the pixel effective brightness mean value of each of the above portrait target areas, including:
  • the average value of the brightness values of the effective pixels in the above-mentioned portrait target area is not less than the first brightness threshold and not For pixels greater than the second brightness threshold, the first brightness threshold is equal to the regional brightness mean minus the regional standard deviation, the second brightness threshold is equal to the regional brightness mean plus the regional standard deviation, and the regional brightness mean and the regional standard deviation are respectively the above The mean and standard deviation of the brightness values of all pixels within the portrait target area.
  • the above-mentioned calculation and acquisition of the secondary exposure time based on the current exposure time, the over-exposure brightness threshold and the above-mentioned pixel effective brightness average value include:
  • the secondary exposure time is calculated and obtained, wherein the secondary exposure time is equal to the product of the effective average brightness of the image and the current exposure time divided by the over-exposure brightness threshold.
  • the above calculation of the mean value of the mean value of the pixel effective brightness of all the above-mentioned portrait target regions is used as the mean value of the effective brightness of the image, including:
  • k is a positive integer between 1 and N
  • L(k) represents the kth element of the pixel effective brightness average value array
  • N represents the total number of the above-mentioned portrait target areas
  • L' represents the effective brightness average value of the above-mentioned image
  • the brightness mean value array is an array composed of the pixel effective brightness mean values of all the above-mentioned portrait target regions.
  • the above calculation obtains the secondary exposure time, including:
  • T' is the above-mentioned secondary exposure time
  • T is the current exposure time corresponding to the above-mentioned image to be processed
  • L1 is the above-mentioned overexposure brightness threshold
  • L' is the average value of the effective brightness of the above-mentioned image.
  • the aforementioned acquisition of a secondary exposure image based on the aforementioned secondary exposure time, and acquisition of a target image after completion of overexposure correction processing based on the aforementioned overexposed image and the aforementioned secondary exposure image including:
  • the above-mentioned overexposed image is corrected based on the above-mentioned double-exposure image to obtain a target image.
  • the above-mentioned shooting is performed based on the above-mentioned secondary exposure time to obtain a secondary exposure image, including:
  • the camera is controlled to shoot based on the above-mentioned secondary exposure time, and the image obtained by shooting is used as the above-mentioned secondary exposure image.
  • the above-mentioned overexposed image is corrected based on the above-mentioned secondary exposure image to obtain a target image, including:
  • a target image is obtained by replacing the overexposed pixels in the overexposed image with corresponding pixels in the double exposure image, wherein the brightness value of the overexposed pixel is greater than the overexposed brightness threshold.
  • the second aspect of the present application provides an image processing device, wherein the above-mentioned device includes:
  • An over-exposed image acquisition module configured to acquire an over-exposed image, and obtain the portrait target area in the above-mentioned over-exposed image
  • Mean value acquisition module used to respectively obtain the pixel effective luminance mean value of each above-mentioned portrait target area
  • the secondary exposure time acquisition module is used to calculate and obtain the secondary exposure time based on the current exposure time, the overexposure brightness threshold and the above-mentioned pixel effective brightness average;
  • a processing module configured to acquire a secondary exposure image based on the secondary exposure time, and acquire a processed target image based on the overexposed image and the secondary exposure image.
  • a third aspect of the present application provides a computer-readable storage medium, where an image processing program is stored on the computer-readable storage medium, and when the image processing program is executed by a processor, any one of the steps of the above-mentioned image processing method is implemented.
  • the overexposed image is obtained, and the portrait target area in the above overexposed image is obtained; the pixel effective brightness average value of each of the above portrait target areas is obtained respectively; based on the current exposure time, the overexposure brightness threshold and the above-mentioned
  • the second exposure time is obtained by calculating the mean value of the effective brightness of the pixels; a second exposure image is obtained based on the above second exposure time, and a target image after overexposure correction processing is obtained based on the above overexposure image and the above second exposure image.
  • the secondary exposure time corresponding to the current overexposed image is obtained, and after the secondary exposure image is obtained based on the secondary exposure time, the current overexposed image and the Obtained double exposure image Acquisition of a target image after overexposure correction processing is conducive to recording objects with large brightness differences in the same scene in the same target image, which is conducive to improving the quality of the obtained target image. Clearness, improve image recording effect.
  • FIG. 1 is a schematic flow diagram of an image processing method provided in an embodiment of the present application
  • FIG. 2 is a schematic flowchart of step S100 in FIG. 1 of the embodiment of the present application.
  • FIG. 3 is a schematic flowchart of step S104 in FIG. 2 of the embodiment of the present application.
  • FIG. 4 is a schematic diagram of the brightness value distribution corresponding to a portrait target area provided by the embodiment of the present application.
  • Fig. 5 is a specific flow diagram of step S300 in Fig. 1 of the embodiment of the present application.
  • Fig. 6 is a specific flow diagram of step S400 in Fig. 1 of the embodiment of the present application.
  • FIG. 7 is a schematic flow chart of an image processing method provided in an embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of an image processing device provided in an embodiment of the present application.
  • FIG. 9 is a functional block diagram of an internal structure of a smart terminal provided by an embodiment of the present application.
  • the term “if” may be construed as “when” or “once” or “in response to determining” or “in response to detecting” depending on the context.
  • the phrases “if determined” or “if detected [the described condition or event]” may be construed, depending on the context, to mean “once determined” or “in response to the determination” or “once detected [the described condition or event]” event]” or “in response to detection of [described condition or event]”.
  • a camera is an essential and important device in a smart classroom system.
  • the camera in a smart classroom captures the teaching process of the teacher and is used for teaching recording and remote streaming.
  • the display device of the smart classroom sometimes cannot record normally because the brightness is too high.
  • the exposure time is usually adjusted when the picture is overexposed, so as to obtain an image with better display effect.
  • the problem with the existing technology is that simply adjusting the exposure time, no matter how you adjust it, can’t record the subjects with large brightness differences in the same scene well in the same frame, which is not conducive to improving the clarity of the obtained image, and affects Image recording effect.
  • the convolution method is also used for image restoration, but the convolution method consumes a lot of exposure time and cannot be applied to real-time recording in dynamic scenes. The failure to record the display screen information will cause incomplete recording of the teaching content, remote students cannot observe the teaching content on the display screen, etc., which will affect the normal teaching function and user experience.
  • the overexposed image is obtained, and the portrait target area in the above-mentioned overexposed image is obtained; the pixel effective brightness mean value of each of the above-mentioned portrait target areas is obtained respectively; based on the current exposure time, the overexposure The brightness threshold and the average value of the effective brightness of the above pixels are calculated to obtain the secondary exposure time; the secondary exposure image is obtained based on the secondary exposure time, and a target after the overexposure correction process is obtained based on the above overexposure image and the above secondary exposure image image.
  • the secondary exposure time corresponding to the current overexposed image is obtained, and after the secondary exposure image is obtained based on the secondary exposure time, the current overexposed image and the Obtained double exposure image Acquisition of a target image after overexposure correction processing is conducive to recording objects with large brightness differences in the same scene in the same target image, which is conducive to improving the quality of the obtained target image. Clearness, improve image recording effect.
  • the embodiment of the present application provides an image processing method, specifically, the above method includes the following steps:
  • Step S100 acquiring an overexposed image, and acquiring a portrait target area in the overexposed image.
  • the above-mentioned overexposed image is an image obtained by photographing a target object with partial area overexposure
  • the target object is an object that needs to be recorded through the image.
  • the application scenario of a smart classroom is taken as an example for illustration, and the target objects include teachers and students in the classroom and display screens, and may also include areas containing teaching information such as blackboards.
  • the target object may also be other objects.
  • the target object may include participants and a conference playback display screen, which is not specifically limited here.
  • the aforementioned portrait target area is an area corresponding to a human face in the overexposed image.
  • the current camera usually adjusts the automatic exposure based on the face.
  • the exposure corresponding to the face area is usually normal, and there will not be too strong overexposure. Therefore, obtaining the target area of the portrait in the overexposed image is helpful to quickly Pixels with normal brightness in the over-exposed image are obtained, so as to facilitate knowing the degree of over-exposure of the over-exposed image, thereby facilitating adjustment of the secondary exposure time, and compensation and correction of the over-exposed area.
  • the faces in the overexposed image include the faces of the teacher and the faces of the students.
  • step S200 obtain the pixel effective luminance mean value of each of the above-mentioned portrait target areas respectively.
  • a portrait target area corresponds to a pixel effective mean brightness, which is the mean value of the brightness values of all effective pixels in the corresponding portrait target area, wherein an effective pixel is a pixel that is neither too dark nor too bright.
  • valid pixels are pixels whose luminance values are within a preset range in the corresponding portrait target area.
  • the mean value of effective brightness of pixels corresponding to each portrait target area is calculated and acquired respectively.
  • Step S300 calculating and obtaining a secondary exposure time based on the current exposure time, the overexposure brightness threshold, and the above average pixel effective brightness.
  • the exposure time is the time for the shutter to be opened in order to project light onto the photosensitive surface of the photographic photosensitive material.
  • the above-mentioned current exposure time is the exposure time corresponding to the current over-exposed image, that is, the above-mentioned over-exposed image is an image obtained by shooting based on the current exposure time.
  • the overexposure brightness threshold is a preset brightness threshold. Considering the situation of overexposure, when the brightness value corresponding to a certain pixel exceeds the above-mentioned overexposure brightness threshold, it is considered that the point is overexposed.
  • the above-mentioned overexposure brightness threshold may be set and adjusted according to actual needs.
  • the current exposure time can be directly reduced as the second exposure time, so as to acquire information of partially overexposed objects in the scene by means of the second lower exposure time.
  • the secondary exposure time is accurately calculated based on the current exposure time, the overexposure brightness threshold, and the above average pixel effective brightness, so as to ensure that the information of locally overexposed objects in the scene can be fully obtained, and at the same time reduce
  • the required waiting and calculation time can improve real-time performance and meet the real-time performance requirements of the classroom.
  • step S400 a secondary exposure image is acquired based on the secondary exposure time, and a target image after overexposure correction processing is acquired based on the overexposure image and the secondary exposure image.
  • the second exposure image is acquired based on the second exposure time.
  • the secondary exposure time is calculated according to the brightness value of the current overexposed image, which can ensure that in the obtained secondary exposure image, the area corresponding to the overexposed area in the current overexposed image is normal (not overexposed ), so that the over-exposure image and the double-exposure image can be combined to obtain a clearer target image that has completed the over-exposure correction.
  • all target objects in the current scene including the faces of teachers and students and the content displayed on the display screen
  • some content will not be unclear due to overexposure.
  • the overexposed image is obtained, and the portrait target area in the above-mentioned overexposed image is obtained; the pixel effective brightness average value of each of the above-mentioned portrait target areas is obtained respectively; based on the current exposure time, Calculate the over-exposure brightness threshold and the average value of the effective brightness of the above pixels to obtain the secondary exposure time; obtain the secondary exposure image based on the above secondary exposure time, and obtain an image based on the above-mentioned over-exposure image and the above-mentioned secondary exposure image after the over-exposure correction process is completed target image.
  • the secondary exposure time corresponding to the current overexposed image is obtained, and after the secondary exposure image is obtained based on the secondary exposure time, the current overexposed image and the Obtained double exposure image Acquisition of a target image after overexposure correction processing is conducive to recording objects with large brightness differences in the same scene in the same target image, which is conducive to improving the quality of the obtained target image. Clearness, improve image recording effect.
  • the above step S100 includes:
  • Step S101 acquiring an image to be processed.
  • Step S102 acquiring overexposed pixels in the image to be processed based on the overexposure brightness threshold, where the brightness value of the overexposed pixels is greater than the overexposure brightness threshold.
  • Step S103 when the ratio of the number of overexposed pixels in the image to be processed is higher than the preset proportion of overexposed pixels, the image to be processed is used as an overexposed image.
  • Step S104 acquiring the portrait target area in the above-mentioned overexposed image.
  • the image to be processed is an image that requires image processing
  • the image to be processed is an image obtained by shooting a target object in a target scene (such as a smart classroom scene) through a camera.
  • the image to be processed may be an image with an overexposure problem, or an image without an overexposure problem. Therefore, in this implementation, it is necessary to determine whether the image to be processed is an overexposed image.
  • the first image of the current scene that is, the image to be processed
  • the image resolution is X ⁇ Y
  • the image to be processed includes X ⁇ Y pixels.
  • the color space of the image to be processed is transformed into an HSL model, where L is a brightness value.
  • L is a brightness value.
  • the L brightness value range in the HSL model is fixed at 0-1.0, regardless of the color depth, and is suitable for the exposure degree analysis in this embodiment.
  • the above-mentioned overexposure brightness threshold is preset to be 0.9.
  • the pixel For a certain pixel in the image to be processed, when its brightness value L exceeds 0.9, the pixel is considered to be overexposed and is regarded as an overexposed pixel. Traversing X ⁇ Y pixels, obtaining all the overexposed pixels and accumulating their number, calculating the proportion of overexposed pixels in all pixels in the image to be processed (ie, the proportion of the number), when the number of overexposed pixels accounts for
  • the ratio is higher than the preset overexposure pixel ratio, the image to be processed is processed as an overexposed image; otherwise, the image to be processed is considered normal and no processing is required, and the image to be processed is directly used as the target image.
  • the preset ratio of overexposed pixels is 10%. When the overexposed pixels exceed 10% of the total pixels in the image to be processed, it is considered that some areas of the image to be processed are overexposed, and image correction processing is required. .
  • the above step S104 includes:
  • Step S1041 perform face recognition on the above-mentioned overexposed image.
  • step S1042 the regions corresponding to the recognized faces are respectively used as the above-mentioned target regions of the portrait.
  • the current camera usually adjusts the automatic exposure based on the face.
  • the exposure corresponding to the face area is usually normal, and there will not be too strong overexposure. Therefore, in this embodiment, the overexposure image obtained through face recognition face target area to facilitate subsequent image correction.
  • the above-mentioned portrait target area includes the area corresponding to the teacher and the area corresponding to the student, assuming that the total number of the portrait target area in the above-mentioned overexposed image is N, the brightness value L in the HSL model corresponding to each pixel in the N portrait target area Record sequentially to obtain the queue ROI[N].
  • the above-mentioned step S200 includes: for each of the above-mentioned portrait target areas, calculating the average value of the brightness values of the effective pixels in the above-mentioned portrait target area, as the pixel effective brightness average value of the above-mentioned portrait target area, wherein the above-mentioned A valid pixel is a pixel whose luminance value is not less than the first luminance threshold and not greater than the second luminance threshold, the first luminance threshold is equal to the regional luminance mean minus the regional standard deviation, and the above second luminance threshold is equal to the regional luminance mean plus the regional standard deviation , the above-mentioned area brightness mean value and the above-mentioned area standard deviation are respectively the mean value and the standard deviation of the brightness values of all pixels in the above-mentioned portrait target area.
  • each portrait target area in the ROI queue most of the image pixels are valid data, but also contain a small amount of overexposed or dark background or edge pixels, and the brightness distribution in each portrait target area is approximately normal distribution.
  • the effective pixels are pixels whose luminance values are within an effective range (that is, within the range formed by the first luminance threshold and the second luminance threshold).
  • the brightness values corresponding to all the pixels in the area are obtained.
  • the queue head data in the ROI queue are processed, and the brightness values of all pixels in each portrait target area are respectively obtained.
  • the brightness values of all its pixels can be respectively formed into a brightness value array ROI_L[n], where n represents the total number of pixels in the portrait target area.
  • Fig. 4 is a schematic diagram of the brightness value distribution corresponding to a portrait target area provided by the embodiment of the present application, where p is the number of pixels of each brightness value L, ⁇ is the mean value of the normal distribution, and ⁇ is the standard deviation of the normal distribution.
  • the mean value of the above-mentioned regional brightness is the mean value ⁇ of the normal distribution
  • the above-mentioned regional standard deviation is the standard deviation ⁇ of the normal distribution.
  • the mean value ⁇ and standard deviation ⁇ are calculated and obtained based on the following formulas (1) and (2):
  • Lmax is the maximum value of the brightness value in the target area of the current portrait
  • i represents the current brightness value, from 0 to Lmax, represents the value of all brightness values traversed
  • p(i) represents the number of pixels with brightness value i
  • n represents the total number of pixels in the current portrait target area.
  • j is used for counting, j is taken from 1 to n
  • ROI_L(j) represents the jth element in the brightness value array ROI_L
  • the first element of the array ROI_L in this embodiment is ROI_L(1), that is, counting starts from 1 .
  • the first brightness threshold is ⁇ - ⁇
  • the second brightness threshold is ⁇ + ⁇ .
  • the brightness value L is within [ ⁇ - ⁇ , ⁇ + ⁇ ]
  • the brightness value is an effective brightness value
  • the corresponding pixel It is an effective pixel
  • the luminance value not in this interval is the interference luminance value.
  • only effective luminance values are used to calculate the average pixel effective luminance in each portrait target area, thereby improving calculation accuracy, avoiding interference from disturbing luminance values, and obtaining significant luminance values of each portrait target area.
  • calculate the average value of the pixel effective brightness in each portrait target area based on the following formula (3):
  • A represents the effective average brightness of pixels in a portrait target area
  • i represents the current brightness value
  • p(i) represents the number of pixels with brightness value i
  • n represents the total number of pixels in the current portrait target area.
  • the calculated luminance data of the portrait target area may be released, and the corresponding head of the queue ROI[N] may be removed from the queue to save storage space. At the same time, it can also be judged according to the queue ROI[N] whether all the portrait target areas have been calculated. When the queue ROI[N] in the memory is empty, it is considered that the pixel effective brightness mean array L[ N].
  • the above step S300 includes:
  • Step S301 calculating the mean value of the average pixel effective brightness of all the above-mentioned portrait target areas, as the average effective brightness of the image.
  • Step S302 calculating and obtaining a secondary exposure time, wherein the secondary exposure time is equal to the product of the effective image brightness average and the current exposure time divided by the over-exposure brightness threshold.
  • k is used for counting, k is taken from 1 to N, L(k) represents the kth element of the pixel effective brightness mean array, and the first element of the pixel effective brightness mean value array is L(1), that is, starting from 1 Count, N represents the total number of portrait object regions.
  • T′ is the second exposure time
  • T is the current exposure time
  • L 1 is the overexposure brightness threshold
  • the overexposure brightness threshold is set to 0.9.
  • the above step S400 includes:
  • Step S401 shooting based on the above-mentioned secondary exposure time, and acquiring a secondary exposure image.
  • Step S402 correcting the above-mentioned over-exposed image based on the above-mentioned double-exposure image, and acquiring a target image.
  • the camera is controlled to take a second shot of the current scene based on the second exposure time obtained by the above calculation, so that a partially overexposed area can be clearly displayed in the second exposure image.
  • the target image is obtained by replacing the overexposed pixels in the overexposed image with corresponding pixels in the double exposure image, wherein the brightness value of the overexposed pixel is greater than the overexposed brightness threshold.
  • the correct image after image correction i.e. the target image
  • time complexity of the method in this embodiment is O(X ⁇ Y), which can meet the requirements of real-time processing.
  • X ⁇ Y is the image resolution of the overexposed image.
  • FIG. 7 is a schematic flowchart of an image processing method provided in an embodiment of the present application.
  • the color space is converted to determine whether the auto-exposure image is overexposed (whether q% is greater than 10%, and q% is the proportion of overexposed pixels ).
  • the process is performed based on the specific process shown in Figure 7 to obtain the second exposure time, and then the second exposure image is obtained, and the current image is corrected based on the second exposure image, thereby obtaining the correct image ( i.e. the target image).
  • the scene information is obtained by continuously adjusting the exposure time through scene brightness analysis, but when there are objects with significant brightness differences in the same scene, this exposure method cannot capture objects with different brightness in the same frame at the same time .
  • image inpainting techniques using convolution methods multiple convolutions will actually result in more frequent exposures, which can only be applied to image inpainting of static scenes.
  • the image processing method in this embodiment uses the HSL model to analyze the brightness of the picture.
  • the time complexity of the algorithm is O(X ⁇ Y), and the analysis work can be completed with imperceptible time delay. This low-delay algorithm can satisfy Real-time image inpainting for dynamic scenes.
  • the image processing method proposed in this embodiment reduces the frame rate, obtains significant exposure values (i.e., effective brightness values) based on face recognition technology, and simultaneously converts the entire picture information into an HSL mathematical model to facilitate the analysis of the brightness of each part of the image.
  • the information of the partially over-exposed object in the scene is obtained by means of the second low exposure time, and finally the two images are stitched together to record the object with different brightness in the same scene. on screen.
  • the above image processing method can also be used in other camera shooting scenes with a display, such as smart conference scenes, etc., and the above image processing method can be used to solve the problem that the display is too bright in the scene and the information on the display cannot be captured. question.
  • an embodiment of the present application further provides an image processing device, and the above image processing device includes:
  • the overexposure image acquisition module 510 is configured to acquire the overexposure image, and acquire the portrait target area in the overexposure image.
  • the above-mentioned overexposed image is an image obtained by photographing a target object with partial area overexposure
  • the target object is an object that needs to be recorded through the image.
  • the application scenario of a smart classroom is taken as an example for illustration, and the target objects include teachers and students in the classroom and display screens, and may also include areas containing teaching information such as blackboards.
  • the target object may also be other objects.
  • the target object may include participants and a conference playback display screen, which is not specifically limited here.
  • the aforementioned portrait target area is an area corresponding to a human face in the overexposed image.
  • the current camera usually adjusts the automatic exposure based on the face.
  • the exposure corresponding to the face area is usually normal, and there will not be too strong overexposure. Therefore, obtaining the target area of the portrait in the overexposed image is helpful to quickly Pixels with normal brightness in the over-exposed image are obtained, so as to facilitate knowing the degree of over-exposure of the over-exposed image, thereby facilitating adjustment of the secondary exposure time, and compensation and correction of the over-exposed area.
  • the faces in the overexposed image include the faces of the teacher and the faces of the students.
  • the mean value acquisition module 520 is configured to respectively acquire the mean value of the pixel effective brightness of each of the above-mentioned portrait target areas.
  • a portrait target area corresponds to a pixel effective mean brightness, which is the mean value of the brightness values of all effective pixels in the corresponding portrait target area, wherein an effective pixel is a pixel that is neither too dark nor too bright.
  • valid pixels are pixels whose luminance values are within a preset range in the corresponding portrait target area.
  • the average pixel effective brightness corresponding to each portrait target area is calculated and acquired respectively.
  • the second exposure time acquiring module 530 is configured to calculate and acquire the second exposure time based on the current exposure time, the overexposure brightness threshold and the above-mentioned pixel effective brightness average.
  • the exposure time is the time for the shutter to be opened in order to project light onto the photosensitive surface of the photographic photosensitive material.
  • the above-mentioned current exposure time is the exposure time corresponding to the current over-exposed image, that is, the above-mentioned over-exposed image is an image obtained by shooting based on the current exposure time.
  • the overexposure brightness threshold is a preset brightness threshold. Considering the situation of overexposure, when the brightness value corresponding to a certain pixel exceeds the above-mentioned overexposure brightness threshold, it is considered that the point is overexposed.
  • the above-mentioned overexposure brightness threshold may be set and adjusted according to actual needs.
  • the current exposure time can be directly reduced as the second exposure time, so as to acquire information of partially overexposed objects in the scene by means of the second lower exposure time.
  • the secondary exposure time is accurately calculated based on the current exposure time, the overexposure brightness threshold, and the above average pixel effective brightness, so as to ensure that the information of locally overexposed objects in the scene can be fully obtained, and at the same time reduce
  • the required waiting and calculation time can improve real-time performance and meet the real-time performance requirements of the classroom.
  • the processing module 540 is configured to acquire a secondary exposure image based on the secondary exposure time, and acquire a processed target image based on the overexposed image and the secondary exposure image.
  • the second exposure image is acquired based on the second exposure time.
  • the secondary exposure time is calculated according to the brightness value of the current overexposed image, which can ensure that in the obtained secondary exposure image, the area corresponding to the overexposed area in the current overexposed image is normal (not overexposed ), so that the over-exposure image and the double-exposure image can be combined to obtain a clearer target image that has completed the over-exposure correction.
  • all target objects in the current scene including the faces of teachers and students and the content displayed on the display screen
  • some content will not be unclear due to overexposure.
  • the image processing device acquires the overexposed image through the overexposed image acquisition module 510, and acquires the target area of the portrait in the above-mentioned overexposed image; the average value acquisition module 520 respectively acquires the values of the target areas of the above-mentioned portraits.
  • the second exposure time is obtained by calculating and obtaining the second exposure time based on the current exposure time, the overexposure brightness threshold and the above-mentioned pixel effective luminance mean value through the second exposure time acquisition module 530; the second exposure image is obtained based on the above-mentioned second exposure time through the processing module 540 , and acquire a processed target image based on the above-mentioned over-exposure image and the above-mentioned double-exposure image.
  • the secondary exposure time corresponding to the current overexposed image is obtained, and after the secondary exposure image is obtained based on the secondary exposure time, the current overexposed image and the Obtained double exposure image Acquisition of a target image after overexposure correction processing is conducive to recording objects with large brightness differences in the same scene in the same target image, which is conducive to improving the quality of the obtained target image. Clearness, improve image recording effect.
  • the present application also provides an intelligent terminal, the functional block diagram of which may be shown in FIG. 9 .
  • the above intelligent terminal includes a processor, a memory, a network interface and a display screen connected through a system bus.
  • the processor of the smart terminal is used to provide calculation and control capabilities.
  • the memory of the smart terminal includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system and an image processing program.
  • the internal memory provides an environment for the operation of the operating system and the image processing program in the non-volatile storage medium.
  • the network interface of the smart terminal is used to communicate with external terminals through a network connection. When the image processing program is executed by the processor, the steps of any one of the above image processing methods are implemented.
  • the display screen of the smart terminal may be a liquid crystal display screen or an electronic ink display screen.
  • an intelligent terminal includes a memory, a processor, and an image processing program stored on the above-mentioned memory and operable on the above-mentioned processor.
  • an image processing program stored on the above-mentioned memory and operable on the above-mentioned processor.
  • a secondary exposure image is acquired based on the secondary exposure time, and a target image after overexposure correction processing is acquired based on the overexposure image and the secondary exposure image.
  • An embodiment of the present application also provides a computer-readable storage medium, where an image processing program is stored on the above-mentioned computer-readable storage medium, and when the above-mentioned image processing program is executed by a processor, any image processing method provided by the embodiment of the present application is implemented. step.
  • the disclosed apparatus/terminal device and method may be implemented in other ways.
  • the device/terminal device embodiments described above are only illustrative.
  • the division of the above-mentioned modules or units is only a logical function division.
  • other division methods may be used, such as multiple units or Components may be combined or integrated into another system, or some features may be omitted, or not implemented.
  • the above-mentioned integrated modules/units are realized in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the present application realizes all or part of the processes in the methods of the above embodiments, and can also be completed by instructing related hardware through computer programs.
  • the above computer programs can be stored in a computer-readable storage medium. When executed by the processor, the steps in the above-mentioned various method embodiments can be realized.
  • the above-mentioned computer program includes computer program code, and the above-mentioned computer program code may be in the form of source code, object code, executable file or some intermediate form.
  • the above-mentioned computer-readable medium may include: any entity or device capable of carrying the above-mentioned computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random Access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the above computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.
  • the image processing method, device, and computer-readable storage medium provided in the embodiments of the present application acquire the secondary exposure time corresponding to the current overexposed image, and after acquiring the secondary exposure image based on the secondary exposure time, combine the current overexposed image and the obtained Obtain a target image after the over-exposure correction processing of the double-exposure image, and realize the correction processing of the over-exposure image, so that the subjects with large brightness differences in the same scene can be well recorded in the same target image In the actual effect, the clarity of the image has been significantly improved, and the image recording effect has been improved.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Image Processing (AREA)
  • Studio Devices (AREA)

Abstract

L'invention concerne un procédé et un appareil de traitement d'images et un support de stockage lisible par ordinateur. Le procédé comprend : l'acquisition d'une image surexposée et l'acquisition d'une zone cible de portrait dans l'image surexposée (S100) ; l'acquisition d'une valeur moyenne de luminosité effective de pixel de chaque zone cible de portrait (S200) : l'acquisition, par calcul, d'un temps d'exposition secondaire sur la base d'un temps d'exposition actuel, d'un seuil de luminosité surexposée et de la valeur moyenne de luminosité effective de pixel (S300) ; l'acquisition d'une image d'exposition secondaire sur la base du temps d'exposition secondaire, et sur la base de l'image surexposée et de l'image d'exposition secondaire, l'acquisition d'une image cible après qu'un traitement de correction de surexposition est terminé (S400). Dans le présent procédé, des objets photographiés présentant une grande différence de luminosité dans la même scène sont bien enregistrés dans la même image cible de sorte que le degré de netteté de l'image cible obtenue est augmenté et l'effet d'enregistrement d'image est amélioré.
PCT/CN2021/139608 2021-10-12 2021-12-20 Procédé et appareil de traitement d'image, et support de stockage lisible par ordinateur WO2023060762A1 (fr)

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