Mid Sweden University

miun.sePublications
Change search
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
A TV regularisation sparse light field reconstruction model based on guided-filtering
School of Science, Beijing Jiaotong University, Beijing 100044, China.
School of Science, Beijing Jiaotong University, Beijing 100044, China.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology. (Realistic3D)ORCID iD: 0000-0003-3751-6089
School of Science, Beijing Jiaotong University, Beijing 100044, China.
2022 (English)In: Signal processing. Image communication, ISSN 0923-5965, E-ISSN 1879-2677, Vol. 109, article id 116852Article in journal (Refereed) Published
Abstract [en]

Obtaining and representing the 4D light field is important for a number of computer vision applications. Due to the high dimensionality, acquiring the light field directly is costly. One way to overcome this deficiency is to reconstruct the light field from a limited number of measurements. Existing approaches involve either a depth estimation process or require a large number of measurements to obtain high-quality reconstructed results. In this paper, we propose a total variation (TV) regularisation sparse model with the alternating direction method of multipliers (ADMM) based on guided filtering, which addresses this depth-dependence problem with only a few measurements. As one of the sparse optimisation methods, TV regularisation based on ADMM is well suited to solve ill-posed problems such as this. Moreover, guided filtering has good edge-preserving smoothing properties, which can be incorporated into the light field reconstruction process. Therefore, high precision light field reconstruction is established with our model. Specifically, the updated image in the iteration step contains the guidance image, and an initialiser for the least squares method using a QR factorisation (LSQR) algorithm is involved in one of the subproblems. The model outperforms other methods in both visual assessments and objective metrics – in simulation experiments from synthetic data and photographic data using produced focal stacks from light field contents – and it works well in experiments using captured focal stacks. We also show a further application for arbitrary refocusing by using the reconstructed light field.

Place, publisher, year, edition, pages
2022. Vol. 109, article id 116852
Keywords [en]
Light field reconstruction, Total variation regularisation, guided filter
National Category
Signal Processing Media and Communication Technology
Identifiers
URN: urn:nbn:se:miun:diva-45834DOI: 10.1016/j.image.2022.116852ISI: 000860683700002Scopus ID: 2-s2.0-85137158712OAI: oai:DiVA.org:miun-45834DiVA, id: diva2:1688054
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-10-06Bibliographically approved

Open Access in DiVA

fulltext(4497 kB)9 downloads
File information
File name FULLTEXT01.pdfFile size 4497 kBChecksum SHA-512
d0cfab1ffef6498956b4b85045e0be0b40b607fe0b7f73c19704228628404fd3a539982e4fa8a9645733e5c815637aa90b45cc62edacbb3133217d108325ae82
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopushttps://www.sciencedirect.com/science/article/pii/S0923596522001333

Authority records

Sjöström, Mårten

Search in DiVA

By author/editor
Sjöström, Mårten
By organisation
Department of Information Systems and Technology
In the same journal
Signal processing. Image communication
Signal ProcessingMedia and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 9 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: 297 hits
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