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Improving image quality by SSIM based increase of run-length zeros in GPGPU JPEG encoding
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.ORCID iD: 0000-0001-9947-1088
2014 (English)In: Conference Record of the Asilomar Conference on Signals Systems and Computers, IEEE Computer Society, 2014, p. 1714-1718Conference paper, Published paper (Refereed)
Abstract [en]

JPEG encoding is a common technique to compress images. However, since JPEG is a lossy compression certain artifacts may occur in the compressed image. These artifacts typically occur in high frequency or detailed areas of the image. This paper proposes an algorithm based on the SSIM metric to improve the experienced quality in JPEG encoded images. The algorithm improves the quality in detailed areas by up to 1.29 dB while reducing the quality in less detailed areas of the image, thereby increasing the overall experienced quality without increasing the image data size. Further, the algorithm can also be used to decrease the file size (by up to 43%) while preserving the experienced image quality. Finally, an efficient GPU implementation is presented. © 2014 IEEE.

Place, publisher, year, edition, pages
IEEE Computer Society, 2014. p. 1714-1718
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
Keywords [en]
Algorithms; Encoding (symbols); Image coding; Image quality; Program processors, Compressed images; File sizes; GPU implementation; High frequency HF; Image data; Lossy compressions; Run length, Image compression
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-10673DOI: 10.1109/ACSSC.2014.7094760ISI: 000370964900309Scopus ID: 2-s2.0-84940492806ISBN: 978-1-4799-8297-4 (print)OAI: oai:DiVA.org:bth-10673DiVA, id: diva2:854345
Conference
48h Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA
Projects
BigData@BTH - Scalable resource-efficient systems for big data analytics
Funder
Knowledge FoundationAvailable from: 2015-09-16 Created: 2015-09-15 Last updated: 2018-02-02Bibliographically approved

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Petersson, StefanGrahn, Håkan

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf