A Prediction Method Based on Video Compression

A prediction method and video compression technology, applied in the fields of digital video signal modification, image communication, electrical components, etc., can solve problems such as the selection of the adaptability of the image to be compressed, affect the compression quality of the image to be compressed, etc., and reduce the theoretical limit entropy, Improved prediction, improved compression quality

Active Publication Date: 2020-10-16
苏州市吴越智博大数据科技有限公司
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, when the texture of the image to be compressed is relatively complex, the existing video compression methods cannot be adaptively selected according to the image to be compressed, thus affecting the compression quality of the image to be compressed

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
  • A Prediction Method Based on Video Compression
  • A Prediction Method Based on Video Compression
  • A Prediction Method Based on Video Compression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0067] See figure 1 , figure 1 It is a schematic flowchart of a prediction method based on video compression provided by an embodiment of the present invention. The forecasting method includes the following steps:

[0068] Setting the size of the MB (Macro Block, macro block) to be predicted is m*n, wherein, m and n are natural numbers greater than zero;

[0069] Predicting the MB to be predicted by using a first prediction mode, and determining a first prediction residual of the MB to be predicted;

[0070] Predict the to-be-predicted MB by using a second prediction mode, and determine a second prediction residual of the to-be-predicted MB;

[0071] respectively obtaining the first standard deviation corresponding to the first prediction mode and the second standard deviation corresponding to the second prediction mode;

[0072] Determine the final prediction mode of the MB to be predicted according to the first prediction residual, the first standard deviation, the secon...

Embodiment 2

[0091] See figure 2 , figure 2 It is a schematic diagram of an adaptive template of an adaptive prediction method provided by an embodiment of the present invention. The establishment of the template includes the following steps:

[0092] Step 1. Define the number of adaptive template lists;

[0093] The number of epitopes in the self-adaptive template can be 4, 8, 16 or 32; the present invention takes the number of epitopes as 16 as an example, and the same is true for other numbers of epitopes. The number of epitopes in the adaptive template is 16, and the epitope numbers are arranged in order from 0 to 15. The smaller the number, the higher the priority. Each epitope records a set of reconstruction values ​​of one MB. The size of MB can be set as m*n, wherein, m and n are natural numbers greater than zero. In this embodiment, the size of MB is 16*1 as an example, that is, the size of each MB is 16*1 pixels, that is There are 16 reconstruction values ​​per MB.

[0094...

Embodiment 3

[0112] See image 3 , image 3 It is a schematic diagram of an adaptive template of another adaptive prediction method provided by an embodiment of the present invention. The establishment of the template includes the following steps:

[0113] Step 1. Define the number of template lists;

[0114] Define the number of adaptive template epitopes as 4, 8, 16 or 32. The present invention is illustrated by taking the number of adaptive template epitopes as 8 as an example, and the same applies to other numbers of adaptive template epitopes. For the adaptive template epitopes whose number is 8, the epitope numbers are arranged in order from 0 to 7, the smaller the sequence number, the higher the priority, and each epitope records a set of reconstruction values ​​of one MB. The size of the MB can be set. In this embodiment, the size of 8*2 is taken as an example, that is, the size of each MB is 8*2 pixels, that is, each MB has 8*2 reconstruction values.

[0115] Step 2. Update t...

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 relates to a video compression-based prediction method, comprising the following steps: setting the size of an MB to be predicted to be m*n; predicting the MB to be predicted by using afirst prediction mode, and determining a first prediction residual of the MB to be predicted; using a second prediction mode to determine the MB to be predicted, and determining a second prediction residual of the MB to be predicted; respectively obtaining a first standard deviation corresponding to the first prediction mode and a second standard deviation corresponding to the second prediction mode; and determining a final prediction mode of the MB to be predicted according to the first prediction residual, the first standard deviation, the second prediction residual and the second standard deviation. The method has the beneficial effects that when having relatively complex texture, the image to be compressed is predicted by different prediction methods, and then the optimal prediction method is selected from a plurality of prediction methods according to the prediction result, which can reduce the theory ultimate entropy, improve the compression quality of the image to be compressedwith complex texture, and improve the prediction effect.

Description

technical field [0001] The present invention relates to the technical field of video compression, in particular to a prediction method based on video compression. Background technique [0002] The demand for digital video products has been increasing in recent years. The mainstream applications mainly include video communication, security monitoring and industrial automation, etc., and the most popular entertainment applications, such as DVD, HDTV, satellite TV, high-definition (HD) set-top boxes, Internet video streaming, digital cameras and HD camcorders, video discs libraries (video jukebox), high-end displays (LCD, plasma displays, DLP), and personal video cameras. Exciting new applications are also currently being designed or pre-deployed, such as High Definition DVD (Blu-ray / HD-DVD) and Digital Video Broadcasting for home and handheld devices and terrestrial / satellite standards (DVB-T, DVB-H, DMB) , high-definition video phones, digital cameras, and IP set-top boxes....

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 Patents(China)
IPC IPC(8): H04N19/50H04N19/52H04N19/70H04N19/42
CPCH04N19/42H04N19/50H04N19/52H04N19/70
Inventor 冉文方李雯
Owner 苏州市吴越智博大数据科技有限公司
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