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

Adaptive Texture Gradient Prediction Method in Bandwidth Compression

A technology of bandwidth compression and prediction method, which is applied in the field of compression and can solve problems such as small prediction residuals and poor correlation

Active Publication Date: 2021-05-18
XIAN CREATION KEJI CO LTD
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the existing texture correlation prediction method, for the macroblock (Macroblock, MB for short) at the texture boundary in the image, since the current MB and the surrounding MB are not in the same texture area, the correlation between the current MB and the surrounding MB is poor , that is, the correlation between the current MB and the surrounding MB cannot be used to obtain a smaller prediction residual

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
  • Adaptive Texture Gradient Prediction Method in Bandwidth Compression
  • Adaptive Texture Gradient Prediction Method in Bandwidth Compression
  • Adaptive Texture Gradient Prediction Method in Bandwidth Compression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] See figure 1 , figure 1 It is a schematic flow chart of an adaptive texture gradient prediction method in bandwidth compression provided by an embodiment of the present invention; this embodiment describes in detail a prediction method provided by the present invention, and the prediction method includes the following steps:

[0035] Step 1. Select N sampling methods to sample the current MB, where the value of N is a natural number greater than 1;

[0036] Step 2. Predict the current MB, and obtain the prediction residual of the current MB;

[0037] Step 3, calculating the residual absolute value sum of the current MB;

[0038] Step 4. Determine the sampling mode of the current MB according to the absolute sum of the residuals.

[0039] Preferably, the sampling method is an equidistant sampling method.

[0040] Wherein, step 2 may include the following steps:

[0041] Step 21. Predict the sampling points of the current MB, and obtain a first prediction residual of...

Embodiment 2

[0052] See figure 2 and image 3 , figure 2 A schematic diagram of a sampling method of an adaptive texture gradient prediction method provided by an embodiment of the present invention; image 3 It is a schematic diagram of an adaptive texture gradient prediction method provided by an embodiment of the present invention. This embodiment describes in detail a prediction method provided by the present invention on the basis of the above embodiments, and the prediction method includes the following steps:

[0053] Step 1. Define the size in MB

[0054] Define the size of MB as m*n pixel components, where m≥1, n≥1;

[0055] Preferably, the size of MB can be defined as 8*1 pixel component, 16*1 pixel component, 32*1 pixel component, 64*1 pixel component; in this embodiment, the size of MB is 16*1 pixel The component is used as an example for illustration, and the same applies to other MBs of different sizes. The pixel components in the MB are arranged sequentially from lef...

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 present invention relates to a method for predicting adaptive texture gradients in bandwidth compression, comprising: selecting N sampling methods to sample the current MB, wherein the value of N is a natural number greater than 1; predicting the current MB, and obtaining the The prediction residual of the current MB; calculating the sum of the absolute value of the residual of the current MB; and determining the sampling mode of the current MB according to the sum of the absolute value of the residual. The present invention adopts multiple sampling methods for the current MB to obtain the prediction residual and SAD of the current MB. When processing a compressed image with a complex texture, for the current MB at the texture boundary of the current image to be compressed, due to the differences between the current MB and the surrounding MB Not in the same texture area, resulting in a poor correlation between the current MB and surrounding MBs, but the present invention does not depend on the MBs around the current MB based on the texture gradient principle, but obtains the prediction residual through the texture characteristics of the current MB itself, It can improve the accuracy of prediction residual value for complex texture area.

Description

technical field [0001] The invention relates to the technical field of compression, in particular to an adaptive texture gradient prediction method in bandwidth compression. Background technique [0002] Today, with the rapid development of communication technology, multimedia has been integrated into people's life and work. With the transformation of video from analog to digital, people also have higher and higher requirements on the clarity, fluency and real-time of video quality. The amount of digital video information is huge, and it will occupy a huge storage space and channel bandwidth, which restricts the expansion of the video communication industry. In a channel with limited bandwidth, using compression coding technology to reduce the amount of transmitted data is an important means to improve communication speed. [0003] The goal of the bandwidth compression technology is to increase the compression factor as much as possible with a smaller logic area cost, and ...

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): H04N19/132H04N19/50H04N19/182H04N19/176H04N19/103
CPCH04N19/103H04N19/132H04N19/176H04N19/182H04N19/50
Inventor 罗瑜张莹冉文方
Owner XIAN CREATION KEJI 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