Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image compression method based on multilayer convolutional neural network

A convolutional neural network and image compression technology, applied in the field of image processing, can solve the problem that the video compression algorithm has not been greatly improved, and achieve the effect of reducing training time and improving accuracy

Inactive Publication Date: 2019-07-26
JINAN INSPUR HIGH TECH TECH DEV CO LTD
View PDF4 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] At present, with the rapid development of the Internet and mobile phones, many media giants such as YouTube, Toutiao, and Weibo have emerged, making images and videos occupy most of the Internet traffic, so image compression algorithms are becoming more and more important, but traditional video compression The algorithm has been basically perfect and there is not much room for improvement. In this case, it is particularly important to use the current popular deep learning technology to improve image compression

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
  • Image compression method based on multilayer convolutional neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the protection of the present invention. scope.

[0028] The present invention is an image compression technology based on a deep convolutional neural network, and its main goal is to design an image compression codec based on a deep convolutional neural network, and design corresponding quantization methods, entropy coding, etc., to achieve better images compression.

[0029] mainly includes:

[003...

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 provides an image compression method based on a multilayer convolutional neural network, belongs to the technical field of image processing. A cascade algorithm system on the basis of the deep neural network is introduced, the training time is accelerated, the training effect is improved, the working efficiency is greatly improved, so that simple and tedious work is automatic, and the time is saved.

Description

technical field [0001] The invention relates to image processing technology, in particular to an image compression method based on a multi-layer convolutional neural network. Background technique [0002] The reason why image data can be compressed is because there is redundancy in the data. The redundancy of image data is mainly manifested as: spatial redundancy caused by the correlation between adjacent pixels in the image; temporal redundancy caused by correlation between different frames in the image sequence; correlation caused by different color planes or spectral bands. spectrum redundancy. The purpose of data compression is to reduce the number of bits required to represent data by removing these data redundancies. Due to the huge amount of image data, it is very difficult to store, transmit and process, so image data compression is very important. [0003] The information age has brought "information explosion", which greatly increases the amount of data. Therefo...

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): H04N19/124H04N19/13H04N19/147H04N19/42H04N19/89
CPCH04N19/124H04N19/13H04N19/147H04N19/42H04N19/89
Inventor 于治楼戴鸿君
Owner JINAN INSPUR HIGH TECH TECH DEV CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com