Fast Subpixel Motion Estimation Based on Human Visual System

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Intelligent Systems Pub Date : 2024-10-18 DOI:10.1155/2024/6168548
Dadvar Hosseini Avashanagh, Mehdi Nooshyar, Saeed Barghandan, Majid Ghandchi
{"title":"Fast Subpixel Motion Estimation Based on Human Visual System","authors":"Dadvar Hosseini Avashanagh,&nbsp;Mehdi Nooshyar,&nbsp;Saeed Barghandan,&nbsp;Majid Ghandchi","doi":"10.1155/2024/6168548","DOIUrl":null,"url":null,"abstract":"<div>\n <p>More than 80% of video coding times are consumed by motion estimation calculations, which are the most complex aspect of the process. This method eliminates temporal redundancies in a video sequence to achieve maximum compression. Numerous efforts have been made to bring calculations closer to real time, yielding fruitful results. This study proposes a fast subpixel motion estimation algorithm for video encoding with fewer search points. This method employs the capabilities of human visual systems (HVSs), physical motion characteristics of real-world objects, and special image information from successive frames. The number of search points (NSP) using the statistical data of the movement of the blocks in the frames of video sequences is reduced to apply fewer calculations to the system while maintaining the quality of images. Therefore, it is possible to approach fast and real-time calculations instead of time-consuming algorithms by accurately modeling this algorithm.</p>\n </div>","PeriodicalId":14089,"journal":{"name":"International Journal of Intelligent Systems","volume":"2024 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6168548","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/6168548","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

More than 80% of video coding times are consumed by motion estimation calculations, which are the most complex aspect of the process. This method eliminates temporal redundancies in a video sequence to achieve maximum compression. Numerous efforts have been made to bring calculations closer to real time, yielding fruitful results. This study proposes a fast subpixel motion estimation algorithm for video encoding with fewer search points. This method employs the capabilities of human visual systems (HVSs), physical motion characteristics of real-world objects, and special image information from successive frames. The number of search points (NSP) using the statistical data of the movement of the blocks in the frames of video sequences is reduced to apply fewer calculations to the system while maintaining the quality of images. Therefore, it is possible to approach fast and real-time calculations instead of time-consuming algorithms by accurately modeling this algorithm.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于人类视觉系统的快速子像素运动估计
超过 80% 的视频编码时间消耗在运动估计计算上,而运动估计计算是整个过程中最复杂的环节。这种方法可以消除视频序列中的时间冗余,从而实现最大程度的压缩。为了使计算更接近实时,人们做出了许多努力,并取得了丰硕的成果。本研究为视频编码提出了一种搜索点较少的快速子像素运动估计算法。该方法利用了人类视觉系统(HVS)的能力、真实世界物体的物理运动特征以及连续帧的特殊图像信息。在保持图像质量的前提下,利用视频序列帧块运动的统计数据来减少搜索点(NSP)的数量,从而减少系统的计算量。因此,通过对该算法进行精确建模,有可能接近快速和实时计算,而不是耗时的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Intelligent Systems
International Journal of Intelligent Systems 工程技术-计算机:人工智能
CiteScore
11.30
自引率
14.30%
发文量
304
审稿时长
9 months
期刊介绍: The International Journal of Intelligent Systems serves as a forum for individuals interested in tapping into the vast theories based on intelligent systems construction. With its peer-reviewed format, the journal explores several fascinating editorials written by today''s experts in the field. Because new developments are being introduced each day, there''s much to be learned — examination, analysis creation, information retrieval, man–computer interactions, and more. The International Journal of Intelligent Systems uses charts and illustrations to demonstrate these ground-breaking issues, and encourages readers to share their thoughts and experiences.
期刊最新文献
K-Means Centroids Initialization Based on Differentiation Between Instances Attributes ViT-AMD: A New Deep Learning Model for Age-Related Macular Degeneration Diagnosis From Fundus Images Switched Observer-Based Event-Triggered Safety Control for Delayed Networked Control Systems Under Aperiodic Cyber attacks An Innovative Application of Swarm-Based Algorithms for Peer Clustering Deepfake Detection Based on the Adaptive Fusion of Spatial-Frequency Features
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1