An optimized JPEG-XT-based algorithm for the lossy and lossless compression of 16-bit depth medical image. (February 2021)
- Record Type:
- Journal Article
- Title:
- An optimized JPEG-XT-based algorithm for the lossy and lossless compression of 16-bit depth medical image. (February 2021)
- Main Title:
- An optimized JPEG-XT-based algorithm for the lossy and lossless compression of 16-bit depth medical image
- Authors:
- Li, Zhongqiang
Ramos, Alexandra
Li, Zheng
Osborn, Michelle L.
Li, Xin
Li, Yanping
Yao, Shaomian
Xu, Jian - Abstract:
- Highlights: Optimize JPEG-XT algorithms (OPT_JPEG-XT) by the amplification of DCT coefficients. OPT_JPEG-XT could achieve both lossy and lossless compression of medical images. OPT_JPEG-XT can achieve a better compression efficiency than JPEG2000 and conventional JPEG-XT. Small integers in DCT coefficients, discarded in the conventional JPEG-XT, are important to compress 16-bit depth medical images. Abstract: JPEG-based compression is the most widely used image compression algorithm. Previously, JPEG-XT-based work focused on 16-bit depth high-dynamic satellite infrared images, but not on medical images. In this study, we represent an optimized JPEG-XT method (OPT_JPEG-XT) that better compresses 16-bit depth medical images by amplifying (N times) discrete cosine transform (DCT) coefficients. The results show that the small integers and the first two decimal portions of DCT coefficients play important roles in the compression of medical images. By using the appropriate N and number of decimal portions (NDP), OPT_JPEG-XT could realize lossless compression of medical images. Regarding upper and lower 8-bit subimages, the upper subimages have more important roles in the improvement of OPT_JPEG-XT performance than the lower subimages; lower subimages could occupy over 90% sizes of the entire encoding files. Thus, OPT_JPEG-XT could save about 60% of storage space with high PSNR (peak signal-noise-ratio, over 100) and low MSE (mean-square-error, less than 0.08) by decreasing theHighlights: Optimize JPEG-XT algorithms (OPT_JPEG-XT) by the amplification of DCT coefficients. OPT_JPEG-XT could achieve both lossy and lossless compression of medical images. OPT_JPEG-XT can achieve a better compression efficiency than JPEG2000 and conventional JPEG-XT. Small integers in DCT coefficients, discarded in the conventional JPEG-XT, are important to compress 16-bit depth medical images. Abstract: JPEG-based compression is the most widely used image compression algorithm. Previously, JPEG-XT-based work focused on 16-bit depth high-dynamic satellite infrared images, but not on medical images. In this study, we represent an optimized JPEG-XT method (OPT_JPEG-XT) that better compresses 16-bit depth medical images by amplifying (N times) discrete cosine transform (DCT) coefficients. The results show that the small integers and the first two decimal portions of DCT coefficients play important roles in the compression of medical images. By using the appropriate N and number of decimal portions (NDP), OPT_JPEG-XT could realize lossless compression of medical images. Regarding upper and lower 8-bit subimages, the upper subimages have more important roles in the improvement of OPT_JPEG-XT performance than the lower subimages; lower subimages could occupy over 90% sizes of the entire encoding files. Thus, OPT_JPEG-XT could save about 60% of storage space with high PSNR (peak signal-noise-ratio, over 100) and low MSE (mean-square-error, less than 0.08) by decreasing the compression efficiency of lower subimages. Compared to the conventional JPEG-XT and JPEG 2000, OPT_JPEG-XT can acquire a similar compression performance (PSNR > 100, MSE < 0.9, SSR (saving space rate, >60%) to JPEG 2000 when using N = 20 for lower subimages and lossless compression of upper subimages. OPT_JPEG-XT could obtain high SSR (about 90%, similar to traditional JPEG-XT) with with much smaller MSE (25 times lower than conventional JPEG-XT). Therefore, OPT_JPEG-XT could be developed a novel compression method that could realize the lossless and lossy compression of medical images. … (more)
- Is Part Of:
- Biomedical signal processing and control. Volume 64(2021)
- Journal:
- Biomedical signal processing and control
- Issue:
- Volume 64(2021)
- Issue Display:
- Volume 64, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 64
- Issue:
- 2021
- Issue Sort Value:
- 2021-0064-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- JPEG-XT -- Medical image compression -- DCT amplification -- 16-bit depth medical image
Signal processing -- Periodicals
Biomedical engineering -- Periodicals
Signal Processing, Computer-Assisted -- Periodicals
Image Processing, Computer-Assisted -- Periodicals
Biomedical Engineering -- Periodicals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/17468094 ↗
http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%2329675%232006%23999989998%23626449%23FLA%23&_cdi=29675&_pubType=J&_auth=y&_acct=C000045259&_version=1&_urlVersion=0&_userid=836873&md5=664b5cf9a57fc91971a17faf20c32ec1 ↗ - DOI:
- 10.1016/j.bspc.2020.102306 ↗
- Languages:
- English
- ISSNs:
- 1746-8094
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2087.880400
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- 23002.xml