{"title":"使用有损形状编码、sa预测和sa块的形状自适应图像压缩","authors":"Li-Ang Chen, Jian-Jiun Ding, Yih-Cherng Lee","doi":"10.1109/APSIPA.2016.7820772","DOIUrl":null,"url":null,"abstract":"As the annoying blocking or ghost artifacts tend to appear in the conventional compression approaches either in the JPEG or JPEG2000 standards at low bitrate, the concept of the object-oriented image compression is proposed. This kind of methods is able to retain the image structural boundaries and therefore has relatively good visual qualities even in high compression ratios. In this paper, we propose a shape-adaptive image compression scheme employing an efficient lossy contour compression algorithm to encode the region information, which is usually the main overhead data in such systems. In addition, the prediction and deblocking techniques commonly used in novel compression approaches are also applied with the proposed shape-adaptive versions. Simulation results suggest that the proposed compression system is able to provide compressed images with much better visual qualities and more reasonable degradation forms compared to other prevailing methods.","PeriodicalId":409448,"journal":{"name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Shape-adaptive image compression using lossy shape coding, SA-prediction, and SA-deblocking\",\"authors\":\"Li-Ang Chen, Jian-Jiun Ding, Yih-Cherng Lee\",\"doi\":\"10.1109/APSIPA.2016.7820772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the annoying blocking or ghost artifacts tend to appear in the conventional compression approaches either in the JPEG or JPEG2000 standards at low bitrate, the concept of the object-oriented image compression is proposed. This kind of methods is able to retain the image structural boundaries and therefore has relatively good visual qualities even in high compression ratios. In this paper, we propose a shape-adaptive image compression scheme employing an efficient lossy contour compression algorithm to encode the region information, which is usually the main overhead data in such systems. In addition, the prediction and deblocking techniques commonly used in novel compression approaches are also applied with the proposed shape-adaptive versions. Simulation results suggest that the proposed compression system is able to provide compressed images with much better visual qualities and more reasonable degradation forms compared to other prevailing methods.\",\"PeriodicalId\":409448,\"journal\":{\"name\":\"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2016.7820772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2016.7820772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shape-adaptive image compression using lossy shape coding, SA-prediction, and SA-deblocking
As the annoying blocking or ghost artifacts tend to appear in the conventional compression approaches either in the JPEG or JPEG2000 standards at low bitrate, the concept of the object-oriented image compression is proposed. This kind of methods is able to retain the image structural boundaries and therefore has relatively good visual qualities even in high compression ratios. In this paper, we propose a shape-adaptive image compression scheme employing an efficient lossy contour compression algorithm to encode the region information, which is usually the main overhead data in such systems. In addition, the prediction and deblocking techniques commonly used in novel compression approaches are also applied with the proposed shape-adaptive versions. Simulation results suggest that the proposed compression system is able to provide compressed images with much better visual qualities and more reasonable degradation forms compared to other prevailing methods.