{"title":"Improved Angle Freeman Chain Code Using Improved Adaptive Arithmetic Coding","authors":"Ji-Ting Wu, Jian-Jiun Ding","doi":"10.1109/APCCAS50809.2020.9301702","DOIUrl":null,"url":null,"abstract":"Binary image is useful in our life. For instance, text, line art, halftone image, tax etc. could use this method, so lossless binary image compression is useful for improve this domain. We found that angle freeman chain code for eight connectivity (AF8) is effective in lossless binary image compression. Therefore, we use improved-adaptive-arithmetic-coding to encode character of AF8, and we also decrease character with global and local frequency table thanks to some characteristics of AF8 we found. Then, in experimental result, we show our proposed method is better than AF8 with static arithmetic coding (SAC), and we also show that the context modeling method we choose is better than the compression coding without context modeling. Furthermore, our method is also better than other method like the ZD code and the AAF8 code.","PeriodicalId":127075,"journal":{"name":"2020 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","volume":"22 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS50809.2020.9301702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Binary image is useful in our life. For instance, text, line art, halftone image, tax etc. could use this method, so lossless binary image compression is useful for improve this domain. We found that angle freeman chain code for eight connectivity (AF8) is effective in lossless binary image compression. Therefore, we use improved-adaptive-arithmetic-coding to encode character of AF8, and we also decrease character with global and local frequency table thanks to some characteristics of AF8 we found. Then, in experimental result, we show our proposed method is better than AF8 with static arithmetic coding (SAC), and we also show that the context modeling method we choose is better than the compression coding without context modeling. Furthermore, our method is also better than other method like the ZD code and the AAF8 code.