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

Video sequence reconstruction method based on compressed sensing

A video sequence and compressed sensing technology, applied in the fields of digital video signal modification, electrical components, image communication, etc., can solve the problem of waste of sampling resources, improve the complexity of codecs, etc., to achieve shortened reconstruction time, good video quality, The effect of a small amount of data

Active Publication Date: 2017-11-17
FUZHOU UNIV
View PDF5 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This not only caused a serious waste of sampling resources, but also greatly increased the complexity of the codec

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
  • Video sequence reconstruction method based on compressed sensing
  • Video sequence reconstruction method based on compressed sensing
  • Video sequence reconstruction method based on compressed sensing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0029] like figure 1 As shown, the present invention provides a method for reconstructing video sequences based on compressed sensing, comprising the steps of:

[0030] (1) Measurement process

[0031] Step A1: grouping the original video sequence into groups of image groups GOP, and dividing them into n image groups;

[0032] Step A2: Set the image group size to m, and the first frame in each image group is the key frame , the second frame to the mth frame are non-key frames , ,…, , i is the serial number of the image group, i=1,2, ...,n;

[0033] Step A3: Sampling the key frames of each image group in blocks at a high sampling rate, corresponding to , i=1,2,...,n, the non-key frames of each image group are sampled in blocks at a low sampling rate, and the corresponding , ,…, , i=1,2,...,n;

[0034] (2) Refactoring process

[0035] ...

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 video sequence reconstruction method based on compressed sensing. An encoding end separates an original video sequence into two types of frames, i.e., key frames and non-key frames, and measurement is performed respectively by use of different sampling rates. At a decoding end, different video sequences are subjected to performance judgement of two different algorithms, i.e., motion estimation / compensation prediction and optical flow method prediction, and then through combination with a comparison result, all the non-key frames are subjected to good-performance algorithm reconstruction by use of inter-frame correlation . When a video is processed, the amount of data needing to be sampled is small and the quality of the recovered video is good. Compared with a traditional algorithm of video independent reconstruction, the peak signal-to-noise ratio at a low sampling rate is improved and the reconstruction time is shortened.

Description

technical field [0001] The invention relates to a video sequence reconstruction method based on compressed sensing. Background technique [0002] In the traditional hybrid coding technology architecture, the video signal is usually fully sampled first, and then compressed, a large amount of redundant data is discarded, leaving only a small amount of important data. This not only causes a serious waste of sampling resources, but also greatly increases the complexity of the codec. Compressed sensing is a new type of information processing theory, which enables the signal to be sampled at a rate much lower than the Nyquist sampling rate, and the original signal can still be reconstructed with a high probability at the decoding end, which can be realized based on a small number of observations Accurate reconstruction of the signal. [0003] In the compressed sensing framework, the core problem is to use the sparsity of the signal to measure and reconstruct the sparse signal cl...

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): H04N19/172H04N19/177H04N19/42H04N19/51
CPCH04N19/172H04N19/177H04N19/42H04N19/51
Inventor 陈建兰诚栋苏忆艳陈淡
Owner FUZHOU UNIV
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