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231225s2017 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2017.2723243
|2 doi
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|a pubmed24n0912.xml
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|a DE-627
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|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Punnappurath, Abhijith
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Multi-Image Blind Super-Resolution of 3D Scenes
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| 264 |
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|c 2017
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 30.07.2018
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|a Date Revised 30.07.2018
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a We address the problem of estimating the latent high-resolution (HR) image of a 3D scene from a set of non-uniformly motion blurred low-resolution (LR) images captured in the burst mode using a hand-held camera. Existing blind super-resolution (SR) techniques that account for motion blur are restricted to fronto-parallel planar scenes. We initially develop an SR motion blur model to explain the image formation process in 3D scenes. We then use this model to solve for the three unknowns-the camera trajectories, the depth map of the scene, and the latent HR image. We first compute the global HR camera motion corresponding to each LR observation from patches lying on a reference depth layer in the input images. Using the estimated trajectories, we compute the latent HR image and the underlying depth map iteratively using an alternating minimization framework. Experiments on synthetic and real data reveal that our proposed method outperforms the state-of-the-art techniques by a significant margin
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| 650 |
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|a Journal Article
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| 700 |
1 |
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|a Nimisha, Thekke Madam
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Rajagopalan, Ambasamudram Narayanan
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 26(2017), 11 vom: 01. Nov., Seite 5337-5352
|w (DE-627)NLM09821456X
|x 1941-0042
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| 773 |
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|g volume:26
|g year:2017
|g number:11
|g day:01
|g month:11
|g pages:5337-5352
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|u http://dx.doi.org/10.1109/TIP.2017.2723243
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|d 26
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