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A srcnn-based inter-frame prediction method

A technology for inter-frame prediction and frame prediction, which is applied in the field of video coding to achieve the effect of image quality enhancement

Active Publication Date: 2021-06-04
HANGZHOU DIANZI UNIV
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  • Claims
  • Application Information

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Problems solved by technology

The present invention aims at inter-frame prediction of image sequences using super-resolution convolutional neural networks

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  • A srcnn-based inter-frame prediction method

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Embodiment Construction

[0026] The present invention mainly focuses on the algorithm innovation of the inter-frame prediction method in video coding, and introduces the training process of the entire model in detail. The specific implementation steps of the present invention will be described in detail below in conjunction with the accompanying drawings. The purpose and effect of the present invention will change more obvious.

[0027] figure 1 It is a schematic diagram of the super-resolution convolutional neural network SRCNN. It can be clearly seen from the figure that the convolutional neural network has a simple structure and can enhance the image quality through nonlinear mapping and image reconstruction. Using this network, the resolution of the image can be improved while performing inter-frame prediction on the image sequence.

[0028] figure 2 It is a flow chart of feature model training of the present invention, wherein specific operations include:

[0029] 1. Collect a large number of...

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Abstract

The invention discloses an SRCNN-based inter-frame prediction method, which is characterized in that the super-resolution convolutional neural network is used to perform inter-frame prediction on image sequences; after performing motion estimation and motion compensation operations on image sequences, combined with super-resolution convolution The feature model is trained by the product neural network; the parameters in the model are used to perform super-resolution reconstruction on the image, and at the same time, the motion estimation and motion compensation are performed on the image to obtain an image consistent with the next frame of the current image. The present invention applies deep learning to inter-frame prediction of video coding, and uses a convolutional neural network to perform feature extraction and training learning for motion estimation and motion compensation operations between image sequences. At the same time, using the super-resolution neural network, the quality of the image will be enhanced when the image is reconstructed.

Description

technical field [0001] The invention belongs to inter-frame prediction in the field of video coding, mainly for improving video transmission efficiency, and specifically relates to an SRCNN-based inter-frame prediction method. Background technique [0002] Super-resolution (Super-Resolution) means converting a low-resolution (Low Resolution) image into a high-resolution (High Resolution) image, usually improving image quality and clarity. Super-Resolution Convolutional Neural Network (SRCNN) is a convolutional neural network applied to image super-resolution reconstruction. By extracting the features of image blocks and nonlinearly mapping the features, a high-resolution image can be reconstructed. resolution image. Since this convolutional neural network was proposed, it has been widely used, and its accuracy and reliability have been well verified. [0003] In today's information age, the research and statistical data of scientists show that about 75% of the information ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/503H04N19/42H04N19/124G06N3/04
CPCH04N19/503H04N19/42H04N19/124G06N3/045
Inventor 颜成钢黄智坤李志胜孙垚棋张继勇张勇东
Owner HANGZHOU DIANZI UNIV
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