A depth-based Multi-view Super-Resolution Method Using Image Fusion and Blind Deblurring Article Swipe
Jun Fan
,
Xiangrong Zeng
,
Qizi Huangpeng
,
Yan Liu
,
Xin Long
,
Jing Feng
,
Zhou Jing-lun
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.3837/tiis.2016.10.027
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.3837/tiis.2016.10.027
Multi-view super-resolution (MVSR) aims to estimate a high-resolution (HR) image from a set of low-resolution (LR) images that are captured from different viewpoints (typically by different cameras).MVSR is usually applied in camera array imaging.Given that MVSR is an ill-posed problem and is typically computationally costly, we super-resolve multi-view LR images of the original scene via image fusion (IF) and blind deblurring (BD).First, we reformulate the MVSR problem into two easier problems: an IF problem and a BD problem.We further solve the IF problem on the premise of calculating the depth map of the desired image ahead, and then solve the BD problem, in which the optimization problems with respect to the desired image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM).Our approach bridges the gap between MVSR and BD, taking advantages of existing BD methods to address MVSR.Thus, this approach is appropriate for camera array imaging because the blur kernel is typically unknown in practice.Corresponding experimental results using real and synthetic images demonstrate the effectiveness of the proposed method.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3837/tiis.2016.10.027
- http://www.itiis.org/digital-library/manuscript/file/21261/TIISVol10No10-27.pdf
- OA Status
- bronze
- Cited By
- 2
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2993462482
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2993462482Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3837/tiis.2016.10.027Digital Object Identifier
- Title
-
A depth-based Multi-view Super-Resolution Method Using Image Fusion and Blind DeblurringWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-10-31Full publication date if available
- Authors
-
Jun Fan, Xiangrong Zeng, Qizi Huangpeng, Yan Liu, Xin Long, Jing Feng, Zhou Jing-lunList of authors in order
- Landing page
-
https://doi.org/10.3837/tiis.2016.10.027Publisher landing page
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https://www.itiis.org/digital-library/manuscript/file/21261/TIISVol10No10-27.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://www.itiis.org/digital-library/manuscript/file/21261/TIISVol10No10-27.pdfDirect OA link when available
- Concepts
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Deblurring, Computer science, Artificial intelligence, Computer vision, Superresolution, Image fusion, Image (mathematics), Resolution (logic), Fusion, Image restoration, Image processing, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1, 2018: 1Per-year citation counts (last 5 years)
- References (count)
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41Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.source.host_organization_name | Korea Society of Internet Information |
| primary_location.source.host_organization_lineage | https://openalex.org/P4323966148 |
| primary_location.source.host_organization_lineage_names | Korea Society of Internet Information |
| primary_location.license | |
| primary_location.pdf_url | http://www.itiis.org/digital-library/manuscript/file/21261/TIISVol10No10-27.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | KSII Transactions on Internet and Information Systems |
| primary_location.landing_page_url | https://doi.org/10.3837/tiis.2016.10.027 |
| publication_date | 2016-10-31 |
| publication_year | 2016 |
| referenced_works | https://openalex.org/W2116361875, https://openalex.org/W1991192972, https://openalex.org/W6770257792, https://openalex.org/W6684033165, https://openalex.org/W1970307692, https://openalex.org/W625228870, https://openalex.org/W2262442824, https://openalex.org/W6630453208, https://openalex.org/W2006462689, https://openalex.org/W2472068831, https://openalex.org/W2166262046, https://openalex.org/W2076441195, https://openalex.org/W2144880842, https://openalex.org/W6677973867, https://openalex.org/W2045079045, https://openalex.org/W2164278908, https://openalex.org/W2135063818, https://openalex.org/W6670815862, https://openalex.org/W6658838613, https://openalex.org/W7000594716, https://openalex.org/W1907897951, https://openalex.org/W3106359998, https://openalex.org/W3099887894, https://openalex.org/W2006262045, https://openalex.org/W2133665775, https://openalex.org/W4244705922, https://openalex.org/W2129990012, https://openalex.org/W2147298660, https://openalex.org/W2082000292, https://openalex.org/W2123031198, https://openalex.org/W2121058967, https://openalex.org/W3043538212, https://openalex.org/W2987004640, https://openalex.org/W2033819227, https://openalex.org/W1507924120, https://openalex.org/W2113137767, https://openalex.org/W3021282624, https://openalex.org/W2059147197, https://openalex.org/W1978259121, https://openalex.org/W2165939075, https://openalex.org/W4292363360 |
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