{"title":"利用粒子群算法分析生物医学图像压缩技术的性能","authors":"J. Maurya, Aanchal Thakur, D. Rathore","doi":"10.1109/ICACAT.2018.8933792","DOIUrl":null,"url":null,"abstract":"Digital images are characterized by multiple parameters. Medical science is one of the most interesting fields for the image compression actually related to the health care sector unit. We proposed a comparative model for the Bio-medical image compression which is better in the terms of result by measuring performance evaluation parameters to increase the value of Peak Signal Noise Ratio, Compression ratio etc. The all experimental process done with these images and finally we compare the all result evaluation performance parameter and chosen the best performance parameter value for the designed proposed techniques.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyze the Performance of Bio-Medical Image Compression Technique using Particle Swarm Optimization\",\"authors\":\"J. Maurya, Aanchal Thakur, D. Rathore\",\"doi\":\"10.1109/ICACAT.2018.8933792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital images are characterized by multiple parameters. Medical science is one of the most interesting fields for the image compression actually related to the health care sector unit. We proposed a comparative model for the Bio-medical image compression which is better in the terms of result by measuring performance evaluation parameters to increase the value of Peak Signal Noise Ratio, Compression ratio etc. The all experimental process done with these images and finally we compare the all result evaluation performance parameter and chosen the best performance parameter value for the designed proposed techniques.\",\"PeriodicalId\":6575,\"journal\":{\"name\":\"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)\",\"volume\":\"1 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACAT.2018.8933792\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACAT.2018.8933792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyze the Performance of Bio-Medical Image Compression Technique using Particle Swarm Optimization
Digital images are characterized by multiple parameters. Medical science is one of the most interesting fields for the image compression actually related to the health care sector unit. We proposed a comparative model for the Bio-medical image compression which is better in the terms of result by measuring performance evaluation parameters to increase the value of Peak Signal Noise Ratio, Compression ratio etc. The all experimental process done with these images and finally we compare the all result evaluation performance parameter and chosen the best performance parameter value for the designed proposed techniques.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
