Block content classification method based on convolution neural network

A technology of convolutional neural network and classification method, which is applied in digital video signal modification, electrical components, image communication, etc., can solve the problem that the content type prediction of coding block needs to be improved, so as to reduce redundant calculation, improve compression quality, and high The effect of accuracy

Inactive Publication Date: 2018-02-06
UNIV OF SCI & TECH OF CHINA
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the accuracy of related methods for predicting the content type of coding blocks needs to be improved.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Block content classification method based on convolution neural network
  • Block content classification method based on convolution neural network
  • Block content classification method based on convolution neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0015] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0016] Some new coding tools are added to the existing screen content coding standards, including palette mode (Palette), intra block matching (Intra Block Copy, IBC) and so on. These tools significantly improve the compression quality, but also greatly increase the encoding complexity. Therefore, it will be a very important and promising method to find an effective method that can not only maintain the compression quality, but also save the encodi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a block content classification method based on a convolution neural network. The method comprises steps of constructing a data set and using the content type of the data set asa tag of a training sample; constructing a convolution neural network; converting the training sample into a gray scale graph; representing each pixel of the gray scale graph by using the eight-bit binary number; extracting the last bit of each pixel to serve as input of the convolution neural network; obtaining a last bit-convolution neural network model through the training; when predicting theinput N*N code blocks, predicting the content type of the current code blocks by use of the last bit-convolution neural network model, and if the output is a camera shooting block, acquiring a classification result; and if the output is a computer generation block, carrying out prediction by use of the last bit-convolution neural network model, and acquiring a classification result of corresponding computer generation text blocks or computer generation non-text blocks. According to the invention, accuracy of prediction of the content type and the calculation efficiency can be improved; redundant calculation can be reduced; and compression quality is improved.

Description

technical field [0001] The present invention relates to the technical field of video coding, in particular to a block content classification method based on a convolutional neural network. Background technique [0002] As one of the deep learning algorithms, convolutional neural network has been widely used in the fields of image classification and pattern recognition. At the same time, the Extended Screen Content Coding (SCC) of High Efficiency Video Coding (HEVC) adopts Palette Mode (Palette) and Intra Block Prediction Mode (IBC) to improve coding efficiency, which inevitably brings a lot of problems. High coding complexity. [0003] Predicting the content type of each coding unit is a key step, although there are some works through which low-level features, such as gradient, variance, entropy, and color number, can be used to classify coding blocks. However, the accuracy of related methods for predicting the content type of coding blocks needs to be improved. Contents...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/176H04N19/90H04N19/85H04N19/593
CPCH04N19/176H04N19/593H04N19/85H04N19/90
Inventor 陈志波叶淑睿
Owner UNIV OF SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap