liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
Block compressive sensing of image and video with nonlocal Lagrangian multiplier and patch-based sparse representation
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Sungkyunkwan University, South Korea.
ungkyunkwan Univ, Sch Elect & Comp Engn, Seoul, South Korea.
Sungkyunkwan Univ, Sch Elect & Comp Engn, Seoul, South Korea.
University of Munster, Germany.
2017 (English)In: Signal processing. Image communication, ISSN 0923-5965, E-ISSN 1879-2677, Vol. 54, p. 93-106Article in journal (Refereed) Published
Abstract [en]

Although block compressive sensing (BCS) makes it tractable to sense large-sized images and video, its recovery performance has yet to be significantly improved because its recovered images or video usually suffer from blurred edges, loss of details, and high-frequency oscillatory artifacts, especially at a low subrate. This paper addresses these problems by designing a modified total variation technique that employs multi-block gradient processing, a denoised Lagrangian multiplier, and patch-based sparse representation. In the case of video, the proposed recovery method is able to exploit both spatial and temporal similarities. Simulation results confirm the improved performance of the proposed method for compressive sensing of images and video in terms of both objective and subjective qualities.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2017. Vol. 54, p. 93-106
Keywords [en]
Block compressive sensing; Distributed compressive video sensing; Total variation; Nonlocal means filter; Sparsifying transform
National Category
Media Engineering
Identifiers
URN: urn:nbn:se:liu:diva-138280DOI: 10.1016/j.image.2017.02.012ISI: 000401202400009OAI: oai:DiVA.org:liu-138280DiVA, id: diva2:1109085
Note

Funding Agencies|National Research Foundation of Korea (NRF) grant - Korean government (MSIP) [2011-001-7578]; MSIP G-ITRC support program [IITP-2016-R6812-16-0001]; ERC via Grant EU FP 7 - ERC Consolidator Grant [615216 LifeInverse]

Available from: 2017-06-13 Created: 2017-06-13 Last updated: 2017-06-28

Open Access in DiVA

fulltext(3991 kB)303 downloads
File information
File name FULLTEXT01.pdfFile size 3991 kBChecksum SHA-512
e557d3161e6c0b7f54e4c2b5f754d63c61e1b3f1282e7bc665692f3ad912c1c1c419b62703f21b1e030c8ea60098f0a1a6e2a6a1847fa6402a287e7968330dec
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Chien, Trinh Van
By organisation
Communication SystemsFaculty of Science & Engineering
In the same journal
Signal processing. Image communication
Media Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 303 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 1050 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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