{"title":"A new real-time pattern selection algorithm for very low bit-rate video coding focusing on moving regions","authors":"M. Paul, M. Murshed, L. Dooley","doi":"10.1109/ICASSP.2003.1199495","DOIUrl":null,"url":null,"abstract":"Very low bit-rate video coding, using regular shaped patterns to focus on moving regions in macroblocks, has gained significant attention recently. This paper presents a new real-time pattern selection (RTPS) algorithm using a large codebook of thirty two patterns. The algorithm uses a relevance measurement for all the patterns and a moving region, to eliminate a large number of irrelevant patterns prior to the actual best likelihood pattern selection procedure. Both theoretically and empirically it is proven that not only is the computational complexity of the new algorithm comparable to the contemporary algorithm that use a pattern codebook size of only eight patterns but also the new algorithm reduces the bit-rate significantly, while maintaining comparable subjective quality.","PeriodicalId":104473,"journal":{"name":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2003.1199495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Very low bit-rate video coding, using regular shaped patterns to focus on moving regions in macroblocks, has gained significant attention recently. This paper presents a new real-time pattern selection (RTPS) algorithm using a large codebook of thirty two patterns. The algorithm uses a relevance measurement for all the patterns and a moving region, to eliminate a large number of irrelevant patterns prior to the actual best likelihood pattern selection procedure. Both theoretically and empirically it is proven that not only is the computational complexity of the new algorithm comparable to the contemporary algorithm that use a pattern codebook size of only eight patterns but also the new algorithm reduces the bit-rate significantly, while maintaining comparable subjective quality.