{"title":"基于方差的可重构模块在内部预测算法中的模式决策","authors":"Vanila Sildas , Premanand Venkatesh Chandramani , R Srinivasan , Rathinam Ananthanarayanan","doi":"10.1016/j.asej.2025.103403","DOIUrl":null,"url":null,"abstract":"<div><div>This work is to design and migrate the hardware architecture implementation from static configuration to dynamic reconfiguration by investigating the viability of five types of intra prediction mode decision based on Similarity index in H.264 video processing. The variance-based five Similarity indices of cosine Similarity, sum of absolute differences (SAD), sum of squared differences (SSD), Hamming distance, and Euclidean distance are proposed to identify the best mode selection in the H.264 intra prediction process. The input parameter for Similarity selection was the variance-based threshold of the original block. The Similarity-based mode decision algorithm is reconfigurable hardware units made to perform nine modes of operations. A reconfigurable hardware implementation of system-on-chip architecture is compared in terms of power usage, resource utilization, and reconfiguration time for all the Similarity procedures. The variance-based hamming distance intra prediction algorithm can achieve 44% computational complexity reduction to select the optimal mode with minimum hardware resource utilisation compared to other proposed techniques.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 7","pages":"Article 103403"},"PeriodicalIF":6.0000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Variance-based reconfigurable modules for mode decision in intra prediction algorithm\",\"authors\":\"Vanila Sildas , Premanand Venkatesh Chandramani , R Srinivasan , Rathinam Ananthanarayanan\",\"doi\":\"10.1016/j.asej.2025.103403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This work is to design and migrate the hardware architecture implementation from static configuration to dynamic reconfiguration by investigating the viability of five types of intra prediction mode decision based on Similarity index in H.264 video processing. The variance-based five Similarity indices of cosine Similarity, sum of absolute differences (SAD), sum of squared differences (SSD), Hamming distance, and Euclidean distance are proposed to identify the best mode selection in the H.264 intra prediction process. The input parameter for Similarity selection was the variance-based threshold of the original block. The Similarity-based mode decision algorithm is reconfigurable hardware units made to perform nine modes of operations. A reconfigurable hardware implementation of system-on-chip architecture is compared in terms of power usage, resource utilization, and reconfiguration time for all the Similarity procedures. The variance-based hamming distance intra prediction algorithm can achieve 44% computational complexity reduction to select the optimal mode with minimum hardware resource utilisation compared to other proposed techniques.</div></div>\",\"PeriodicalId\":48648,\"journal\":{\"name\":\"Ain Shams Engineering Journal\",\"volume\":\"16 7\",\"pages\":\"Article 103403\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2025-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ain Shams Engineering Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2090447925001443\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447925001443","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Variance-based reconfigurable modules for mode decision in intra prediction algorithm
This work is to design and migrate the hardware architecture implementation from static configuration to dynamic reconfiguration by investigating the viability of five types of intra prediction mode decision based on Similarity index in H.264 video processing. The variance-based five Similarity indices of cosine Similarity, sum of absolute differences (SAD), sum of squared differences (SSD), Hamming distance, and Euclidean distance are proposed to identify the best mode selection in the H.264 intra prediction process. The input parameter for Similarity selection was the variance-based threshold of the original block. The Similarity-based mode decision algorithm is reconfigurable hardware units made to perform nine modes of operations. A reconfigurable hardware implementation of system-on-chip architecture is compared in terms of power usage, resource utilization, and reconfiguration time for all the Similarity procedures. The variance-based hamming distance intra prediction algorithm can achieve 44% computational complexity reduction to select the optimal mode with minimum hardware resource utilisation compared to other proposed techniques.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.