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

A Fast Motion Estimation Method

A fast-moving, motion-vector technology, applied in television, electrical components, digital video signal modification, etc., can solve problems such as wasting time, reducing image signal-to-noise ratio, and greatly affecting, so as to achieve wide application, improve search efficiency, and improve speed effect

Inactive Publication Date: 2011-11-30
SICHUAN PANOVASIC TECH
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Among the current search algorithms, the full search algorithm (FS) has the highest estimation accuracy. By searching every candidate point in the matching window, FS can find the global optimal motion vector, but its computational complexity is too high to be conducive to real-time Application; Traditional search algorithms such as three-step search (TSS), hexagonal search (HEXS), and diamond search (DS) are prone to fall into local optimum, unable to find the global optimum, and the search speed cannot be improved
At present, the search algorithms in the existing technology basically adopt the method of directly searching for matching blocks according to the matching criteria, instead of using the statistical probability of predicted motion vectors for priority estimation search, which wastes a lot of time and does not improve efficiency.
Moreover, most of the search algorithms in the prior art use a single-level threshold for termination discrimination. For example, the MVFAST search algorithm uses a fixed single-level threshold 512. This threshold may not be very good for some video sources with complex motion and texture. meet the requirements and have a great impact on the signal-to-noise ratio (PSNR) of the image due to the inability to terminate the discrimination early
Especially for video sequences with complex motion, although the number of search points is reduced, the signal-to-noise ratio of the image is significantly reduced

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 Fast Motion Estimation Method
  • A Fast Motion Estimation Method
  • A Fast Motion Estimation Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0016] The fast motion estimation method in this example uses multiple predicted motion vectors: median motion vector (median MVP), origin motion vector MV(0,0), MV_A (motion vector for block A), MV_B (motion vector for block B) , MV_C (C block motion vector), the previous reference frame corresponds to the block motion vector MV_COL t-1 Or the scaling MV_SC of motion vectors on other reference images. Statistically calculate the probability that the motion vector of the block in the image is equal to these predicted motion vectors. Statistics show that the highest probability is the median MVP, followed by MV(0,0), MV_COL t-1 (Non-zero reference frame is used for multi-frame reference

[0017] MV _ SC = MVref 0 × TRn TR 0

[0018] instead of MV_COL t-1 ), MV_A, MV_B and MV_C. Among them, MVref0 represents the motion vector of the c...

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 video compression technology, in particular to a fast motion estimation method in the video compression technology. The invention proposes a motion estimation method that reduces the possibility of falling into a local optimum and basically does not affect the signal-to-noise ratio of an image. The gist of its technical scheme is: a kind of method for quick motion estimation, comprises the following steps: a. counts the probability size that the motion vector of the block in the image is equal to the predicted motion vector; b. when detecting the motion vector, according to the above steps a Detect the predicted motion vector in sequence from the probability obtained in the statistics from large to small; c. Use a threshold to judge the termination of the motion search. The invention reduces unnecessary searches, improves search efficiency, and is suitable for high-definition video coding and real-time coding.

Description

technical field [0001] The invention relates to video compression technology, in particular to a fast motion estimation method in the video compression technology. Background technique [0002] Motion estimation is one of the most important components in video coding system, and it has an important impact on the quality of coded image sequences. The motion estimation compensation technology can effectively remove the inter-frame redundancy in the image sequence so as to realize effective coding. The motion estimation and compensation technology based on block matching is adopted by many video coding standards, such as MPEG-1 / 2 / 4 and ITU-TH.261 / 263 / 263+ / 264, etc., because of its simple algorithm and easy implementation of software and hardware. The basic idea is to divide the coded image into macroblocks of the same size, and macroblocks can also be divided into smaller blocks. For each block, search for the closest matching block in its reference frame according to a certai...

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): H04N7/26H04N19/513
Inventor 莫启会毛夏飞袁梓瑾鲁国宁
Owner SICHUAN PANOVASIC TECH
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