WO2009121234A1 - Procédé de contrôle de débit de code pour la compression vidéo - Google Patents

Procédé de contrôle de débit de code pour la compression vidéo Download PDF

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Publication number
WO2009121234A1
WO2009121234A1 PCT/CN2008/073089 CN2008073089W WO2009121234A1 WO 2009121234 A1 WO2009121234 A1 WO 2009121234A1 CN 2008073089 W CN2008073089 W CN 2008073089W WO 2009121234 A1 WO2009121234 A1 WO 2009121234A1
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WO
WIPO (PCT)
Prior art keywords
image
complexity factor
bits
rate control
video compression
Prior art date
Application number
PCT/CN2008/073089
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English (en)
Chinese (zh)
Inventor
徐苏珊
Original Assignee
深圳市融创天下科技发展有限公司
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 深圳市融创天下科技发展有限公司 filed Critical 深圳市融创天下科技发展有限公司
Publication of WO2009121234A1 publication Critical patent/WO2009121234A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/147—Data rate or code amount at the encoder output according to rate distortion criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/149—Data rate or code amount at the encoder output by estimating the code amount by means of a model, e.g. mathematical model or statistical model

Definitions

  • the present invention relates to the field of video image processing, and more particularly to a video compression rate control method. Background technique
  • the amount of data of the compressed frame changes, so that the amount of data (code rate) per unit time fluctuates.
  • code rate code rate
  • the principle of rate control is to use a mathematical model to recalculate the quantization factor of the next frame by the currently known user-specified code rate and the number of compressed bits, thereby changing the number of bits after encoding to achieve the purpose of controlling the code rate. .
  • the conventional rate control algorithm (such as the CBR algorithm) includes the following steps: (1) almost uniformly allocating the target number of bits per frame image according to the target bit rate; (2) calculating each frame according to the allocated target number of bits
  • the encoded quantization parameter Qp is derived to ensure that the encoder outputs a constant bit rate. Since the prior art algorithm assigns almost the same number of bits to each frame of the video sequence, in reality, the complexity of each frame image is constantly changing, so that the compressed image quality fluctuates greatly, The image quality is not high, especially in the low-bandwidth/wireless channel. Due to the unstable and error-prone characteristics of the channel itself, the accuracy of the encoder's rate control is put forward.
  • the video compression rate control algorithm comprises the following steps: A. analyzing image features and calculating image feature complexity factors;
  • the step A further includes:
  • A1 Calculating a motion complexity factor of the current image according to the actual number of bits generated by the image coding and the number of output average bits;
  • A3. Combine the current motion complexity factor and texture complexity factor of the image to calculate the feature complexity factor of the current image.
  • the calculation formula is:
  • the average number of coded output bits calculated up to the j-th frame image is the number of coded output average bits up to the j-th frame image, and is the actual number of bits of the j-th frame image coded output, and is the weighting coefficient.
  • the calculation formula of the texture complexity factor of the image in the step A2 is:
  • texture complexity factor of the image which is the absolute difference average of the previous image
  • M is the number of macroblocks in the image
  • ⁇ is the average texture complexity factor up to the jth frame image.
  • ⁇ is the motion complexity factor of the image, and is the texture complexity factor of the image; ; is the adjustment coefficient.
  • the calculation formula of the target number of bits to be allocated in the image in the step B is:
  • the step C further comprises: using the quadratic nonlinear rate-distortion model to obtain the encoded quantization parameter Qp in combination with the number of target bits to be allocated by the image.
  • the invention closely combines the code rate allocation with the feature complexity of the image, so that the encoder can accurately allocate the code rate and improve the control precision of the code rate of the encoder. Meanwhile, the present invention uses the quadratic nonlinear rate distortion.
  • the model obtains the coded quantization parameter Qp, which has better control code rate accuracy than the single linear rate distortion model. Therefore, by using the video compression rate control algorithm of the present invention, the rate control accuracy can be improved, thereby improving the image quality.
  • FIG. 1 is a flowchart of a video compression rate control method of the present invention
  • Fig. 1 is a flow chart showing a video compression rate control method of the present invention, the process is as follows: In step S101, image features are analyzed to calculate image feature complexity factors.
  • FIG. 2 is a flowchart of a video compression rate control method according to an embodiment of the present invention. The method is based on the method flow shown in FIG. 1, and the specific process is as follows:
  • step S201 the motion complexity factor of the current image is calculated based on the actual number of bits generated by the image coding and the number of output average bits.
  • step S203 the feature complexity factor of the current image is calculated in combination with the current motion complexity factor and the texture complexity factor of the image.
  • One embodiment of the present invention uses image feature complexity factors to describe image features, and combines the motion complexity factor of the image with the texture complexity factor to calculate the feature complexity factor of the image.
  • the calculation formula is:
  • C. is the characteristic complexity factor of the image
  • ⁇ is the motion complexity factor of the image
  • ⁇ is the texture complexity factor of the image
  • the encoded quantization parameter Qp is obtained by combining the target number of bits to be allocated by the image and the rate-distortion ("R") model.
  • the encoded quantization parameter Qp is obtained using a quadratic nonlinear RD model in the case where the target number of bits is known, in combination with the number of target bits to be allocated for the image.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Algebra (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

La présente invention concerne un procédé de contrôle de débit de code pour la compression vidéo, appartenant au domaine du traitement d'images vidéo. Le procédé comprend les étapes suivantes : A. l'analyse d'un personnage de l'image, et le calcul du facteur de complexité du personnage de l'image ; B. la combinaison avec le facteur de complexité du personnage de l'image, et le calcul du nombre de bits d'objet nécessaire qui est réparti dans l’image ; C. la combinaison avec le nombre de bits d'objet nécessaire qui est réparti dans l’image en utilisant un modèle de distorsion de débit pour acquérir le paramètre de quantification codé. La présente invention, qui combine étroitement la distribution du débit de code et la complexité du personnage d'une image, et qui acquiert le paramètre de quantification codé Qp à l'aide du modèle de distorsion de débit non linéaire de second ordre, permet d'améliorer la précision de contrôle du débit de code, ce qui permet ensuite d'améliorer la qualité de l'image.
PCT/CN2008/073089 2008-03-31 2008-11-17 Procédé de contrôle de débit de code pour la compression vidéo WO2009121234A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN 200810066409 CN101552917B (zh) 2008-03-31 2008-03-31 一种视频压缩码率控制方法
CN200810066409.8 2008-03-31

Publications (1)

Publication Number Publication Date
WO2009121234A1 true WO2009121234A1 (fr) 2009-10-08

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Cited By (3)

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CN111565317A (zh) * 2019-02-13 2020-08-21 合肥图鸭信息科技有限公司 图像压缩方法、编解码网络训练方法、装置及电子设备
JP2022500901A (ja) * 2018-11-14 2022-01-04 ▲騰▼▲訊▼科技（深▲セン▼）有限公司 符号化の対象となるデータ処理方法、装置、及びコンピュータプログラム
CN113949872A (zh) * 2021-11-09 2022-01-18 华侨大学 一种基于3D-Gradient引导的屏幕内容视频编码码率控制方法

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CN102238382B (zh) * 2010-05-07 2013-09-25 联咏科技股份有限公司 影像压缩的位率控制方法及其装置
CN102025994B (zh) * 2010-12-16 2013-07-03 深圳市融创天下科技股份有限公司 自适应解码复杂度的编码方法、装置、编解码系统和设备
CN102647586B (zh) * 2011-02-16 2015-07-08 富士通株式会社 用在视频编码系统中的码率控制方法和装置
CN103297775B (zh) * 2013-05-17 2016-02-10 西安电子科技大学 基于联合码率分配和控制的多光谱图像压缩系统与方法
CN104427336B (zh) * 2013-09-02 2018-09-14 苏州威迪斯特光电科技有限公司 基于感兴趣区域补偿编码的视频质量提高方法
CN105208388B (zh) * 2014-06-24 2019-03-05 深圳市腾讯计算机系统有限公司 视频通讯中动态调整编码帧率的方法和系统
CN104410861A (zh) * 2014-11-24 2015-03-11 华为技术有限公司 视频编码方法及装置
CN106612434B (zh) * 2015-10-22 2019-06-21 北京博雅华录视听技术研究院有限公司 一种基于视频复杂度的统计复用方法
CN110166781B (zh) * 2018-06-22 2022-09-13 腾讯科技（深圳）有限公司 一种视频编码方法、装置、可读介质和电子设备
CN111787318A (zh) * 2020-06-24 2020-10-16 浙江大华技术股份有限公司 一种视频码率控制方法、装置、设备以及存储装置
CN113691814A (zh) * 2021-07-26 2021-11-23 浙江大华技术股份有限公司 视频编码方法、装置、电子装置和存储介质

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CN1434638A (zh) * 2003-03-08 2003-08-06 华中科技大学 一种视频编码比特率控制方法
CN101069432A (zh) * 2004-12-02 2007-11-07 汤姆逊许可公司 用于视频编码器速率控制的量化参数的确定
CN1767653A (zh) * 2005-11-08 2006-05-03 上海广电（集团）有限公司中央研究院 一种码率控制方法
CN1988659A (zh) * 2006-12-30 2007-06-27 清华大学 一种视频编码码率控制方法

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Publication number Priority date Publication date Assignee Title
JP2022500901A (ja) * 2018-11-14 2022-01-04 ▲騰▼▲訊▼科技（深▲セン▼）有限公司 符号化の対象となるデータ処理方法、装置、及びコンピュータプログラム
JP7163485B2 (ja) 2018-11-14 2022-10-31 ▲騰▼▲訊▼科技（深▲セン▼）有限公司 符号化の対象となるデータ処理方法、装置、及びコンピュータプログラム
CN111565317A (zh) * 2019-02-13 2020-08-21 合肥图鸭信息科技有限公司 图像压缩方法、编解码网络训练方法、装置及电子设备
CN113949872A (zh) * 2021-11-09 2022-01-18 华侨大学 一种基于3D-Gradient引导的屏幕内容视频编码码率控制方法

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