{"title":"Gridding and compression of microarray images.","authors":"Stefano Lonardi, Yu Luo","doi":"10.1109/csb.2004.1332424","DOIUrl":null,"url":null,"abstract":"<p><p>With the recent explosion of interest in microarray technology, massive amounts of microarray images are currently being produced. The storage and the transmission of this type of data are becoming increasingly challenging. Here we propose lossless and lossy compression algorithms for microarray images originally digitized at 16 bpp (bits per pixels) that achieve an average of 9.5 - 11.5 bpp (lossless) and 4.6 - 6.7 bpp (lossy, with a PSNR of 63 dB). The lossy compression is applied only on the background of the image, thereby preserving the regions of interest. The methods are based on a completely automatic gridding procedure of the image.</p>","PeriodicalId":87417,"journal":{"name":"Proceedings. IEEE Computational Systems Bioinformatics Conference","volume":" ","pages":"122-30"},"PeriodicalIF":0.0000,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/csb.2004.1332424","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Computational Systems Bioinformatics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/csb.2004.1332424","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
With the recent explosion of interest in microarray technology, massive amounts of microarray images are currently being produced. The storage and the transmission of this type of data are becoming increasingly challenging. Here we propose lossless and lossy compression algorithms for microarray images originally digitized at 16 bpp (bits per pixels) that achieve an average of 9.5 - 11.5 bpp (lossless) and 4.6 - 6.7 bpp (lossy, with a PSNR of 63 dB). The lossy compression is applied only on the background of the image, thereby preserving the regions of interest. The methods are based on a completely automatic gridding procedure of the image.