{"title":"感知无损图像压缩与错误恢复","authors":"C. Kwan, Eric Shang, T. Tran","doi":"10.1145/3271553.3271602","DOIUrl":null,"url":null,"abstract":"In many bandwidth constrained applications, lossless compression may be unnecessary, as only two to three times of compression can be achieved. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our first objective is to compare and select the best compression algorithm in the literature to achieve 8:1 compression ratio with perceptually lossless compression for still images. Our second objective is to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in communication channels. We have clearly achieved the above objectives using realistic images.","PeriodicalId":414782,"journal":{"name":"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Perceptually Lossless Image Compression with Error Recovery\",\"authors\":\"C. Kwan, Eric Shang, T. Tran\",\"doi\":\"10.1145/3271553.3271602\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In many bandwidth constrained applications, lossless compression may be unnecessary, as only two to three times of compression can be achieved. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our first objective is to compare and select the best compression algorithm in the literature to achieve 8:1 compression ratio with perceptually lossless compression for still images. Our second objective is to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in communication channels. We have clearly achieved the above objectives using realistic images.\",\"PeriodicalId\":414782,\"journal\":{\"name\":\"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3271553.3271602\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3271553.3271602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Perceptually Lossless Image Compression with Error Recovery
In many bandwidth constrained applications, lossless compression may be unnecessary, as only two to three times of compression can be achieved. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our first objective is to compare and select the best compression algorithm in the literature to achieve 8:1 compression ratio with perceptually lossless compression for still images. Our second objective is to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in communication channels. We have clearly achieved the above objectives using realistic images.