{"title":"Low-cost color space based image compression algorithm for capsule endoscopy","authors":"Nithin Varma Malathkar, S. Soni","doi":"10.1109/ISPCC.2017.8269688","DOIUrl":null,"url":null,"abstract":"An efficient compression algorithm for the capsule endoscopy is described in this paper. This paper consists of a simplified YUV color space, which is developed by taking endoscopy images unique properties into consideration. This is built on RGB-sYUV color conversion, differential pulse code modulation (DPCM) and Golomb-Rice encoder. This DPCM doesn't need any extra buffer memory to store one row of images and Golomb-Rice (G-R) code is simple and easily hardware implemented. This algorithm is lossless and give a compression ratio (CR) of 68.1%. It gives better results than the standard lossless algorithm regarding complexity and compression ratio in capsule endoscopy applications.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPCC.2017.8269688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
An efficient compression algorithm for the capsule endoscopy is described in this paper. This paper consists of a simplified YUV color space, which is developed by taking endoscopy images unique properties into consideration. This is built on RGB-sYUV color conversion, differential pulse code modulation (DPCM) and Golomb-Rice encoder. This DPCM doesn't need any extra buffer memory to store one row of images and Golomb-Rice (G-R) code is simple and easily hardware implemented. This algorithm is lossless and give a compression ratio (CR) of 68.1%. It gives better results than the standard lossless algorithm regarding complexity and compression ratio in capsule endoscopy applications.
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