{"title":"Generating subject oriented codec by evolutionary approach","authors":"Masaaki Matsumura, Seishi Takamura, H. Jozawa","doi":"10.1109/PCS.2010.5702512","DOIUrl":null,"url":null,"abstract":"Many image/video codecs are constructed by the combination of various coding tools such as block division/scanning, branch selection and entropy coders. Codec researchers are developing new coding tools, and seeking versatile combinations that offer improved coding efficiency for various images/videos. However, because of the huge amount of the combination, deriving the best combination is impossible by man-power seeking. In this paper, we propose an automatic optimization method for deriving the combination that suits for categorized pictures. We prepare some categorised pictures, and optimize the combination for each category. In the case of optimization for lossless image coding, our method achieves a bit-rate reduction of over 2.8% (maximum) compared to the combination that offers the best bit-rate averagely prepared beforehand.","PeriodicalId":255142,"journal":{"name":"28th Picture Coding Symposium","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"28th Picture Coding Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCS.2010.5702512","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Many image/video codecs are constructed by the combination of various coding tools such as block division/scanning, branch selection and entropy coders. Codec researchers are developing new coding tools, and seeking versatile combinations that offer improved coding efficiency for various images/videos. However, because of the huge amount of the combination, deriving the best combination is impossible by man-power seeking. In this paper, we propose an automatic optimization method for deriving the combination that suits for categorized pictures. We prepare some categorised pictures, and optimize the combination for each category. In the case of optimization for lossless image coding, our method achieves a bit-rate reduction of over 2.8% (maximum) compared to the combination that offers the best bit-rate averagely prepared beforehand.