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A Motion Estimation Method Based on Improved Ant Colony Optimization Algorithm

An ant colony optimization algorithm and motion estimation technology, applied in calculation, calculation model, digital video signal modification, etc., can solve problems such as high computational complexity, slow convergence speed, and falling into local optimum

Active Publication Date: 2020-04-21
GUILIN UNIV OF ELECTRONIC TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In order to better balance the search accuracy and search speed, some motion estimation algorithms based on optimization techniques have been proposed successively, but most of them have disadvantages such as slow convergence speed, high computational complexity, and easy to fall into local optimum.

Method used

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  • A Motion Estimation Method Based on Improved Ant Colony Optimization Algorithm
  • A Motion Estimation Method Based on Improved Ant Colony Optimization Algorithm
  • A Motion Estimation Method Based on Improved Ant Colony Optimization Algorithm

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Experimental program
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Embodiment

[0065] refer to figure 1 , a motion estimation method based on an improved ant colony optimization algorithm, comprising the following steps:

[0066] Step S1: Initialize the search population, the initial search population consists of 5 fixed points and 2 random points, refer to figure 2 , image 3 , image 3 The solid circle in the center is the position of the zero vector. About 81.80% of the motion vectors are concentrated in the square within the range of ±2 from the zero vector, and about 77.52% of the motion vectors are concentrated within the rhombus within the range of ±2 from the zero vector. The fixed point is set as Figure 4 as shown, Figure 4 The unit length of the small and medium squares is 1, the solid circle is the corresponding position of the left vertex of the current block in the reference frame, the solid circle is the center position of the fixed point group, the triangle is the remaining 4 fixed point positions, and the random search point i is de...

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Abstract

The invention discloses a motion estimation method based on improved ant colony optimization which is characterized by: step S1, initializing; step S2, detecting a tabu table; step S3, calculating a fitness value corresponding to a current point; step S4, judging whether the current point is the most dominant point or not; step S5, updating concentration of residual pheromone; step S6, updating asolution set according to a greedy criterion; step S7, the worst ant "flipping" to the optimal ant and updating the solution set according to the greedy criterion; step S8, checking whether current iteration times reach the maximum iteration number Tmax or not; and step S9, terminating the iteration. According to the motion estimation method based on improved ant colony optimization, good dynamicbalance can be achieved in the search precision and operation complexity, convergence speed is high, the operation complexity is low, and motion estimation precision is high.

Description

technical field [0001] The invention relates to motion estimation technology based on swarm intelligence optimization, in particular to a motion estimation method based on improved ant colony optimization. Background technique [0002] With the development of information technology, frequent image and video exchanges appear in real life, and its huge amount of data has brought great challenges to today's storage and transmission technology. Therefore, the development of efficient video processing technology has become a top priority. Motion estimation is an important research content of video processing technology, which can effectively reduce the time redundancy between frames in video sequences. The so-called motion estimation is actually to use the characteristics of a large amount of time and space redundancy in the video sequence to calculate the difference between the current frame and the corresponding coordinate points of the reference frame, so as to predict the mot...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/00H04N19/51
CPCG06N3/006H04N19/51
Inventor 覃远年梁仲华
Owner GUILIN UNIV OF ELECTRONIC TECH