WO2019105262A1 - Procédé, appareil et dispositif de traitement de flou d'arrière-plan - Google Patents

Procédé, appareil et dispositif de traitement de flou d'arrière-plan Download PDF

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Publication number
WO2019105262A1
WO2019105262A1 PCT/CN2018/116479 CN2018116479W WO2019105262A1 WO 2019105262 A1 WO2019105262 A1 WO 2019105262A1 CN 2018116479 W CN2018116479 W CN 2018116479W WO 2019105262 A1 WO2019105262 A1 WO 2019105262A1
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WO
WIPO (PCT)
Prior art keywords
area
blurring
target
region
blurred
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PCT/CN2018/116479
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English (en)
Chinese (zh)
Inventor
欧阳丹
谭国辉
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Oppo广东移动通信有限公司
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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
Publication of WO2019105262A1 publication Critical patent/WO2019105262A1/fr

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    • 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
    • G06T5/94—Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/67—Focus control based on electronic image sensor signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof

Definitions

  • a further embodiment of the present application provides a non-transitory computer readable storage medium having a computer program stored thereon, which when executed by a processor, implements a background blurring processing method as described in the above embodiments of the present application.
  • the coordinates of the pixel corresponding to the point A are (30, 50), and in the preview image data of the camera 2, the pixel corresponding to the point A.
  • the contour edge of the shooting body is detected, and the target blurred area in the area to be blurred is determined according to the edge of the contour, wherein the target blurred area includes shooting The contour edge of the subject and the portion of the main image to be blurred.
  • the color of the shooting body area and the area to be blurred is different. Therefore, the contour edge of the shooting body can be determined by detecting the color channel, for example, when the subject is a human face, the face is The area is the color of the human body such as skin color, and the other areas are the colors of other scenes different from the color of the face area. Therefore, the color channel detection algorithm can be used to identify the area where the skin color is located to determine the person in the foreground according to the area covered by the skin color.
  • the outline edge of the face area that is, the outer edge of the area covered by the skin color area is the outline edge of the face area.
  • the pixel points in the first region may be blurred when the second region is blurred.
  • the corresponding second region is determined as the target blur region when the color approximation reaches the preset range, wherein the preset range corresponding to the color approximation
  • the ambiguous processing capability of the terminal device is related. The higher the ambiguity processing capability is, the smaller the value corresponding to the preset range is, and the stronger the ambiguity is, the higher the value corresponding to the preset range is.
  • Step 104 Obtain a target blurring intensity of the target blurring area according to a preset blurring strategy.
  • the edge contour of the shooting body When it is detected that the brightness of the shooting scene is lower than the preset threshold, in order to prevent the edge contour of the shooting body from being blurred, it is detected whether there is a face and a hair area to determine whether the current night portrait is photographed, if not, directly
  • the blurring process of the area to be blurred is performed in a normal manner, and if present, the hair contour edge of the detected portrait is obtained by taking the hair region and the corresponding background sub-region as the boundary of the hair contour edge, and the background sub-region is used as the target blurring region. Further, the blurring weight is gradually increased from the edge of the hair contour to the edge of the hair contour.
  • the edge region of the hair may be blurred due to poor imaging effect, and the background blurring process of the present application is adopted.
  • the edge of the hair is blurred in a dark environment, so that the edges of the hair are not blurred in the blurred image, and the hair and the background portion can be transitioned. Smoother and more natural.
  • FIG. 9 is a schematic structural diagram of a background blur processing device according to an embodiment of the present application. As shown in FIG. 9, the background blur processing device is provided.
  • the first obtaining module 100, the first determining module 200, the second determining module 300, the second obtaining module 400, and the processing module 500 are included.
  • the first determining module 200 is configured to determine, according to the depth of field information and the focus area, the area to be blurred in the main image and the corresponding original blurring intensity.
  • the second determining module 300 is configured to detect a contour edge of the shooting subject in the main image when detecting that the shooting scene brightness is lower than a preset threshold, and determine a target blurring area in the to-be-defined area according to the contour edge.
  • the second obtaining module 400 is configured to obtain a target blurring intensity of the target blurring area according to a preset blurring strategy.
  • the area to be blurred and the corresponding original blurring intensity when detecting that the brightness of the shooting scene is lower than a preset threshold, detecting the contour edge of the shooting subject, and determining the target blurring area in the area to be blurred according to the edge of the contour, according to
  • the preset blurring strategy determines the target blurring intensity of the target blurring area, and then blurs the target blurring area according to the target blurring intensity, and treats the non-target blurring in the blurring area according to the original blurring intensity.
  • the area is blurred. Thereby, the contour edge of the photographing body is prevented from being blurred, and the blurring effect of the image is improved.
  • the present application further provides a computer device, wherein the computer device is any device including a memory including a storage computer program and a processor running the computer program, for example, a smart phone, a personal computer, or the like.
  • the computer device further includes an image processing circuit, and the image processing circuit may be implemented by using hardware and/or software components, and may include various processing units defining an ISP (Image Signal Processing) pipeline.
  • Figure 10 is a schematic illustration of an image processing circuit in one embodiment. As shown in FIG. 10, for convenience of explanation, only various aspects of the image processing technique related to the embodiment of the present application are shown.
  • the ISP processor 1040 processes the raw image data pixel by pixel in a variety of formats.
  • each image pixel can have a bit depth of 8, 10, 12, or 14 bits, and the ISP processor 1040 can perform one or more image processing operations on the raw image data, collecting statistical information about the image data. Among them, image processing operations can be performed with the same or different bit depth precision.
  • ISP processor 1040 When receiving raw image data from sensor 1020 interface or from image memory 1030, ISP processor 1040 can perform one or more image processing operations, such as time domain filtering.
  • the processed image data can be sent to image memory 1030 for additional processing prior to being displayed.
  • the ISP processor 1040 receives the processed data from the image memory 1030 and performs image data processing in the original domain and in the RGB and YCbCr color spaces.
  • the processed image data may be output to display 1070 for viewing by a user and/or further processed by a graphics engine or a GPU (Graphics Processing Unit). Additionally, the output of ISP processor 1040 can also be sent to image memory 1030, and display 1070 can read image data from image memory 1030.
  • image memory 1030 can be configured to implement one or more frame buffers.
  • each functional unit in each embodiment of the present application may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated modules, if implemented in the form of software functional modules and sold or used as stand-alone products, may also be stored in a computer readable storage medium.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Studio Devices (AREA)
  • Image Processing (AREA)

Abstract

La présente invention concerne un procédé, un appareil et un dispositif de traitement de flou d'arrière-plan, le procédé consistant : à acquérir une image principale photographiée par une caméra principale et une image secondaire photographiée par une caméra secondaire et, en fonction de l'image principale et de l'image secondaire, à acquérir des informations de profondeur de champ ; en fonction des informations de profondeur de champ et d'une zone de mise au point, à déterminer une zone à rendre floue dans l'image principale et une intensité de flou initiale correspondante ; lorsqu'il est détecté que la luminosité de scène de photographie est inférieure à un seuil prédéfini, à détecter un bord de contour du sujet de photographie principal et, en fonction du bord de contour, à déterminer une zone de flou cible dans la zone à rendre floue, et à déterminer une intensité de flou cible de la zone de flou cible ; en fonction de l'intensité de flou cible, à exécuter un traitement de flou de la zone de flou cible et, en fonction de l'intensité de flou initiale, à exécuter un traitement de flou des zones de flou non cibles dans la zone à rendre floue. Ainsi, les bords de contour du sujet de photographie principal ne sont pas flous de manière erronée, ce qui permet d'améliorer l'effet de flou de l'image.
PCT/CN2018/116479 2017-11-30 2018-11-20 Procédé, appareil et dispositif de traitement de flou d'arrière-plan WO2019105262A1 (fr)

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CN201711243751.6 2017-11-30
CN201711243751.6A CN107977940B (zh) 2017-11-30 2017-11-30 背景虚化处理方法、装置及设备

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CN113674303A (zh) * 2021-08-31 2021-11-19 Oppo广东移动通信有限公司 图像处理方法、装置、电子设备及存储介质
CN113766090A (zh) * 2020-06-02 2021-12-07 武汉Tcl集团工业研究院有限公司 一种图像处理方法、终端以及存储介质
CN114216656A (zh) * 2021-12-13 2022-03-22 惠州Tcl移动通信有限公司 一种摄像头虚化效果性能测试卡、系统及制备方法
CN116894768A (zh) * 2023-09-11 2023-10-17 成都航空职业技术学院 一种基于人工智能的目标检测优化方法和系统

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CN111080571A (zh) * 2019-11-15 2020-04-28 北京迈格威科技有限公司 摄像头遮挡状态检测方法、装置、终端和存储介质
CN111080571B (zh) * 2019-11-15 2023-10-20 北京迈格威科技有限公司 摄像头遮挡状态检测方法、装置、终端和存储介质
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CN114216656A (zh) * 2021-12-13 2022-03-22 惠州Tcl移动通信有限公司 一种摄像头虚化效果性能测试卡、系统及制备方法
CN116894768A (zh) * 2023-09-11 2023-10-17 成都航空职业技术学院 一种基于人工智能的目标检测优化方法和系统
CN116894768B (zh) * 2023-09-11 2023-11-21 成都航空职业技术学院 一种基于人工智能的目标检测优化方法和系统

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