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Multifunctional video fast coding method based on deep neural network

A deep neural network and fast coding technology, which is applied in the field of multi-functional video fast coding based on deep neural network, can solve problems such as imperfections, achieve a wide range of application scenarios, and reduce the effect of coding time

Active Publication Date: 2022-03-22
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current intra-frame fast coding algorithm suitable for VVC is not perfect enough.

Method used

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  • Multifunctional video fast coding method based on deep neural network
  • Multifunctional video fast coding method based on deep neural network
  • Multifunctional video fast coding method based on deep neural network

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Embodiment Construction

[0040] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0041] The present invention provides a kind of multifunctional video fast encoding method based on deep neural network, comprising the following steps:

[0042] Step S1, judging whether the number of reference depth units reaches a preset value, if so, execute step S2;

[0043] Step S2, predicting the depth map of the current coding unit CU based on the BP neural network (back propagation neural network), and then determining the division depth of the CU according to the depth map information;

[0044] Step S3. Based on the probability model, count the ratio of the number of times of the best coded CU partition mode, and determine the prediction sequence of the current CU partition mode according to the probability from large to small;

[0045] Step S4, calculating the rate-distortion RD cost value and according to the corresponding cos...

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Abstract

The invention relates to a multifunctional video fast encoding method based on a deep neural network. First, by studying the temporal-spatial domain correlation of video content, the back-propagation (BP) neural network is used to predict the CU partition depth; then, the statistical probability is used to select the CU partition mode; Necessary division mode to save encoding time, so as to achieve the purpose of reducing time complexity while ensuring the encoding performance of the encoder remains unchanged.

Description

technical field [0001] The invention belongs to the technical field of video coding, and in particular relates to a multifunctional fast video coding method based on a deep neural network, so as to achieve the purpose of greatly saving coding time without affecting the coding performance of a coder. Background technique [0002] The new-generation Versatile Video Coding Standard (VVC) adopts more technologies to increase the compression rate to solve the conflict between the rapidly increasing video data and the limited bandwidth network transmission environment. However, while improving the coding efficiency, it also increases the computational complexity of the coding. In the VVC encoding process, video images are divided into blocks (coding units (CU)) of different sizes according to content characteristics to improve compression efficiency, and determining the optimal block method of video images will consume a lot of encoding time. Therefore, if the division process of...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/103H04N19/567H04N19/85G06N3/04G06N3/08
CPCH04N19/103H04N19/567H04N19/85G06N3/084G06N3/045
Inventor 赵铁松王楷徐艺文吴陆狄郑权斐
Owner FUZHOU UNIV