Distributed video compressive sensing sampling method based on time correlation

A time-dependent, distributed video technology, applied in the fields of digital video signal modification, electrical components, image communication, etc., can solve the problem of insufficient consideration of the time correlation between video frames, and reduce reconstruction time and delay. , The effect that meets the requirements of real-time video

Active Publication Date: 2017-10-20
NANJING UNIV OF POSTS & TELECOMM
View PDF4 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method solves the problem that the time correlation between video frames is not fully considered in the existing distributed video compression sensing sampling process

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
  • Distributed video compressive sensing sampling method based on time correlation
  • Distributed video compressive sensing sampling method based on time correlation
  • Distributed video compressive sensing sampling method based on time correlation

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0035] Below in conjunction with accompanying drawing, technical solution of the present invention is described in detail, specific embodiment is as follows:

[0036] Such as figure 1 As shown, the present invention provides a distributed video compression sensing sampling method based on temporal correlation, and the specific steps of the method are as follows:

[0037] Input: video sequence, each frame has I c × I r pixels;

[0038] Step 1: Split the original video stream into several image groups (Group of Picture, GOP) with a length of G, and the first frame of each group is X 0is the key frame, and the remaining frames {X 1 ,X 2 ,...,X j ,...,X G-1} is a non-keyframe;

[0039] Step 2: Divide each non-key frame into n blocks of size B×B;

[0040] Step 3: Calculate the structural similarity between every two adjacent non-key frames in an image group: And the proportion of time correlation information of each non-key frame in a GOP to the information in the entire...

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 distributed video compressive sensing sampling method based on time correlation. According to the method, on the basis of establishing a non-feedback distributed video compressive sensing model, the time correlation among video frames is utilized fully; a sampling rate of each block is preliminarily allocated according to a size of the information of a video group of pictures occupied by the information of each picture block; mode judgment is carried out according inter-frame residuals; and a practical sampling rate of each small block is calculated, so self-adaptive sampling allocation is realized. According to the method, the reconstruction quality of a video is improved under the same total sampling rate, the energy saving amount resulting from reducing the sampling times far exceeds the extra energy consumption amount resulting from employing a dynamic sampling rate algorithm, no feedback channel is employed, and the time delay is relatively low. According to the method, the problem that the time correlation is not taken into full consideration in an existing distributed video compressive sensing sampling process is solved, and the method has good practical value.

Description

technical field [0001] The invention relates to a distributed video compression sensing sampling method based on time correlation, and belongs to the technical field of video image processing. Background technique [0002] Due to the complexity of video signal processing and the large transmission traffic, for the application environment lacking power and communication network infrastructure, the existing video surveillance system cannot meet the application needs. Compressive Sensing (CS) technology deeply mines the sparsity inside the video signal, extracts the low-dimensional projection of the original signal through the undersampling method, and uses optimization or iteration to complete the reconstruction of the original signal with high probability. Applying CS to Distributed Video Coding (DVC) produces Distributed Compressive Video Sensing (DCVS), which saves storage space, reduces coding complexity, and improves the quality of video images. [0003] At present, most...

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): H04N19/42H04N19/132H04N19/137H04N19/177H04N19/154
Inventor 张登银杨阳丁飞
Owner NANJING UNIV OF POSTS & TELECOMM
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