{"title":"基于背景图像分割的近无损HDR图像压缩","authors":"Lei Chen, Zhiming Wang","doi":"10.1109/SIPROCESS.2016.7888260","DOIUrl":null,"url":null,"abstract":"High-Dynamic Rang and high spatial resolutions image, such as 16bits X-ray image, is required in security and medical applications. However, transporting this kind of the image costs a lot in network bandwidth, storage capacity and transmission time. To solve the problem, efficient compression technology is raised. In this paper, we propose a nearly lossless compression algorithm with background segmentation for 16 bits X-ray image. Background and foreground of image are separated with a threshold calculated through detecting background peak of image gray histogram. Background pixels connected to image border are segmented as background by two pass run-length labeling. Then image background is compressed with Run-Length-encoding (RLE) and the foreground is encoded via Lempel-Ziv-77 (LZ77). To validate the proposed algorithm, we compare it with state-of-art compression algorithms LZ77, JPGE_LS, and arithmetic coding. Experimental results show that our algorithm obtains good performance both on compress ratio and speed with neglectable information loss.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"76 13","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Nearly lossless HDR images compression by background image segmentation\",\"authors\":\"Lei Chen, Zhiming Wang\",\"doi\":\"10.1109/SIPROCESS.2016.7888260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-Dynamic Rang and high spatial resolutions image, such as 16bits X-ray image, is required in security and medical applications. However, transporting this kind of the image costs a lot in network bandwidth, storage capacity and transmission time. To solve the problem, efficient compression technology is raised. In this paper, we propose a nearly lossless compression algorithm with background segmentation for 16 bits X-ray image. Background and foreground of image are separated with a threshold calculated through detecting background peak of image gray histogram. Background pixels connected to image border are segmented as background by two pass run-length labeling. Then image background is compressed with Run-Length-encoding (RLE) and the foreground is encoded via Lempel-Ziv-77 (LZ77). To validate the proposed algorithm, we compare it with state-of-art compression algorithms LZ77, JPGE_LS, and arithmetic coding. Experimental results show that our algorithm obtains good performance both on compress ratio and speed with neglectable information loss.\",\"PeriodicalId\":142802,\"journal\":{\"name\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"volume\":\"76 13\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIPROCESS.2016.7888260\",\"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 IEEE International Conference on Signal and Image Processing (ICSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPROCESS.2016.7888260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nearly lossless HDR images compression by background image segmentation
High-Dynamic Rang and high spatial resolutions image, such as 16bits X-ray image, is required in security and medical applications. However, transporting this kind of the image costs a lot in network bandwidth, storage capacity and transmission time. To solve the problem, efficient compression technology is raised. In this paper, we propose a nearly lossless compression algorithm with background segmentation for 16 bits X-ray image. Background and foreground of image are separated with a threshold calculated through detecting background peak of image gray histogram. Background pixels connected to image border are segmented as background by two pass run-length labeling. Then image background is compressed with Run-Length-encoding (RLE) and the foreground is encoded via Lempel-Ziv-77 (LZ77). To validate the proposed algorithm, we compare it with state-of-art compression algorithms LZ77, JPGE_LS, and arithmetic coding. Experimental results show that our algorithm obtains good performance both on compress ratio and speed with neglectable information loss.