title: Application of genetic algorithm to hexagon-based motion estimation.
abstract: With the improvement of science and technology, the development of the network, and the exploitation of the HDTV, the demands of audio and video become more and more important. Depending on the video coding technology would be the solution for achieving these requirements. Motion estimation, which removes the redundancy in video frames, plays an important role in the video coding. Therefore, many experts devote themselves to the issues. The existing fast algorithms rely on the assumption that the matching error decreases monotonically as the searched point moves closer to the global optimum. However, genetic algorithm is not fundamentally limited to this restriction. The character would help the proposed scheme to search the mean square error closer to the algorithm of full search than those fast algorithms. The aim of this paper is to propose a new technique which focuses on combing the hexagon-based search algorithm, which is faster than diamond search, and genetic algorithm. Experiments are performed to demonstrate the encoding speed and accuracy of hexagon-based search pattern method and proposed method.
authors.affiliation: Department of Information Technology & Communication, Shih Chien University, No. 200 University Road, Neimen District, Kaohsiung City 84550, Taiwan.
authors.forename: Chih-Ming
authors.identifier: 0000-0002-3012-1917
authors.initials: CM
authors.lastname: Kung
authors.affiliation: Institute of Computer Science & Information Engineering, National Cheng Kung University, No. 1 University Road, Tainan City 70101, Taiwan.
authors.forename: Wan-Shu
authors.initials: WS
authors.lastname: Cheng
authors.affiliation: Department of Information Engineering, I-Shou University, No. 1 Section 1, Syuecheng Road, Dashu District, Kaohsiung City 84001, Taiwan.
authors.forename: Jyh-Horng
authors.identifier: 0000-0003-0026-8333
authors.initials: JH
authors.lastname: Jeng
mesh_terms: D000465:Algorithms; D002875:Chromosomes / Q000235:genetics*; D044962:Data Compression / Q000379:methods; D008957:Models, Genetic; D009038:Motion