Motion estimation method based on genetic search and template matching

Abstract

The invention discloses a motion estimation method based on genetic search and template matching, belonging to the technical field of video compression coding. The method comprises the following steps: adopting multiple methods to predict blocks to be coded in a frame to be coded so as to obtain multiple predicted motion vectors; respectively searching a point directed by each predicted motion vector in a search window, adopting three termination strategies to judge, and if the three termination strategies are met, finishing the search; using an initial template to carry out population initialization, and copying, intersecting and selecting population cycles until genetic termination conditions are met; on the basis, searching adjacent points so as to obtain matched blocks to code the blocks to be coded; and traversing a complete frame image, and coding the complete frame image. In the method, the statistic characteristics of the motion vectors are combined to set the three termination strategies, and the template matching is combined with the genetic search algorithm for use, thus ensuring the coding quality and greatly reducing the time of the motion estimation at the same time.

Description

technical field [0001] The invention belongs to the technical field of video compression coding, and relates to a motion estimation method based on genetic search and template matching. Background technique [0002] Motion estimation is an important part of video compression coding technology, and its role is to effectively remove the temporal redundancy of image sequences. In the process of video compression coding, motion estimation accounts for 50%-70% of the computational load, so improving the efficiency of motion estimation is of great significance for speeding up video coding. [0003] The block matching method is currently the most widely used motion estimation method. By dividing each frame of image into multiple non-overlapping blocks, the block with the highest similarity to the reference block is searched in the search window of the reference frame, and the distance between the two is calculated. The residuals and motion vectors are coded to realize the compress...

AI Technical Summary

Problems solved by technology

However, most of the traditional motion estimation algorithms based on genetic search focus on designing complex encoding methods, fitness functions and genetic operators, which greatly increases the complexity of the algorithm.

Although motion estimation based on genetic algorithm has good global optimization ability, its high algorithm complexity requires huge calculation and storage overhead, which increases the encoding time.

The search time of some improved algorithms is even comparable to that of the full search algorithm, which contradicts the original intention of improving the search speed

And the traditional motion estimation algorithm based on genetic search generally adopts a low number of genetic iterations, although the search speed is relatively improved, but the accuracy of the genetic algorithm is reduced, thus affecting the quality of the encoding

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