Scalable compressive video

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)

Abstract

The paper presents a scalable compressive sampling (CS) scheme for video acquisition. The proposed solution enables progressive reconstruction of video frames with novel measurement matrices. Simulation results show significant performance improvements over the traditional CS technique for the base layer and slightly better performance for the final enhancement layer.

LanguageEnglish
Title of host publicationProceedings of the 18th IEEE International Conference on Image Processing (ICIP)
Place of PublicationNew York
PublisherIEEE
Pages921-924
Number of pages4
ISBN (Print)9781457713040
DOIs
Publication statusPublished - Sep 2011

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Keywords

  • compressive imaging
  • scalable coding
  • compressive sampling
  • scalable compressive video
  • discrete cosine transforms
  • vectors
  • systematics
  • imaging
  • image reconstruction
  • image coding

Cite this

Stankovic, V., Stankovic, L., & Cheng, S. (2011). Scalable compressive video. In Proceedings of the 18th IEEE International Conference on Image Processing (ICIP) (pp. 921-924). New York: IEEE. https://doi.org/10.1109/ICIP.2011.6116710
Stankovic, V. ; Stankovic, L. ; Cheng, S. / Scalable compressive video. Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). New York : IEEE, 2011. pp. 921-924
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Stankovic, V, Stankovic, L & Cheng, S 2011, Scalable compressive video. in Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). IEEE, New York, pp. 921-924. https://doi.org/10.1109/ICIP.2011.6116710

Scalable compressive video. / Stankovic, V.; Stankovic, L.; Cheng, S.

Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). New York : IEEE, 2011. p. 921-924.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Stankovic V, Stankovic L, Cheng S. Scalable compressive video. In Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). New York: IEEE. 2011. p. 921-924 https://doi.org/10.1109/ICIP.2011.6116710