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Fast inter-frame prediction method based on motion estimation and temporal-spatial correlation

A technology of motion estimation and inter-frame prediction, which is applied in the field of HEVC high-definition video encoding, can solve the problems of large amount of calculation and long encoding time of high-definition video, and achieve the effect of wide application, shortening encoding time and remarkable effect

Active Publication Date: 2016-09-21
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

HEVC's inter-frame prediction process is very computationally intensive, and high-definition video encoding takes a long time

Method used

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Embodiment Construction

[0044] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention and are not intended to limit it. this invention.

[0045] The present invention reduces the time of high-definition video coding under the condition that the video coding quality is hardly affected, and is not limited to video sequences with specific features, and does not rely too much on features such as image resolution and texture. In order to illustrate that the present invention does not rely too much on the characteristics of the video itself, and hardly affects the video coding quality, the inventor has carried out experiments on some HM standard test sequences in the environment of the following table 1, and the specific experim...

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Abstract

The invention discloses a fast inter-frame prediction method based on motion estimation and temporal-spatial correlation, comprising the following steps: (1) in terms of motion estimation, two rounds of diamond search respectively at a step length of 1 and at a step length of 2 are carried out with a medium value MV as an initial search point, motion estimation is stopped if an obtained optimal MV is the initial medium value MV, or, a newly obtained optimal MV instead of the medium value MV is used to conduct a TZSearch process; and (2) in terms of PU mode selection and CU depth choice, the coding mode and rate-distortion cost information of nine adjacent blocks of spatial and temporal neighborhoods of a current coding unit are used, and if a certain number of neighborhood coding units adopt a skip mode and the rate-distortion cost of the current coding unit is less than a threshold, that a current block is in a motion flat area is judged, and the PU mode traversal process and CU partition are stopped in advance. The time for high-definition video coding is reduced greatly. The method is not limited to video sequences with specific features, and does not rely too much on the image resolution, texture and other features.

Description

technical field [0001] The present invention relates to the technical field of HEVC high-definition video coding, in particular to a motion estimation and time-space domain correlation-based method that does not affect the quality of video coding, can greatly reduce the time of high-definition video coding, and does not rely too much on image resolution and texture features. Fast Inter Prediction Method. Background technique [0002] Video is a visual, specific and effective information transmission medium. A video sequence can be represented as a three-dimensional matrix, where the two dimensions NxM represent the pixel value of each image, forming the spatial domain of the video, and the other dimension represents the time domain of the video. In order to enable the human eye to have a smooth and continuous experience, the video The frame rate needs to reach 25fps (frames per second). However, the data volume of the original video is very huge, which is greatly limited i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/56H04N19/567
CPCH04N19/56H04N19/567
Inventor 宋锐安亮贾媛李云松王养利赵园伟
Owner XIDIAN UNIV
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