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Coding of plenoptic images by using a sparse set and disparities
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)ORCID iD: 0000-0003-3751-6089
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
2015 (English)In: Proceedings - IEEE International Conference on Multimedia and Expo, IEEE conference proceedings, 2015, -Art. no. 7177510 p.Conference paper, Published paper (Refereed)
Abstract [en]

A focused plenoptic camera not only captures the spatial information of a scene but also the angular information. The capturing results in a plenoptic image consisting of multiple microlens images and with a large resolution. In addition, the microlens images are similar to their neighbors. Therefore, an efficient compression method that utilizes this pattern of similarity can reduce coding bit rate and further facilitate the usage of the images. In this paper, we propose an approach for coding of focused plenoptic images by using a representation, which consists of a sparse plenoptic image set and disparities. Based on this representation, a reconstruction method by using interpolation and inpainting is devised to reconstruct the original plenoptic image. As a consequence, instead of coding the original image directly, we encode the sparse image set plus the disparity maps and use the reconstructed image as a prediction reference to encode the original image. The results show that the proposed scheme performs better than HEVC intra with more than 5 dB PSNR or over 60 percent bit rate reduction.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. -Art. no. 7177510 p.
Keyword [en]
Plenoptic, lightfield, HEVC, compression
National Category
Signal Processing Telecommunications
Identifiers
URN: urn:nbn:se:miun:diva-25034DOI: 10.1109/ICME.2015.7177510ISI: 000380486500133Scopus ID: 2-s2.0-84946061755Local ID: STCISBN: 978-­1-­4799-­7082-­7 (print)OAI: oai:DiVA.org:miun-25034DiVA: diva2:815764
Conference
IEEE International Conference on Multimedia and Expo, ICME 2015; Turin; Italy; 29 June 2015 through 3 July 2015
Available from: 2015-06-01 Created: 2015-06-01 Last updated: 2017-08-22Bibliographically approved

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Li, YunSjöström, MårtenOlsson, Roger
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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