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Fabrizio Pece, and Jan Kautz, Bitmap Movement Detection: HDR for Dynamic Scenes. JVRB - Journal of Virtual Reality and Broadcasting, 10(2013), no. 2. (urn:nbn:de:0009-6-36506)

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%0 Journal Article
%T Bitmap Movement Detection: HDR for Dynamic Scenes
%A Pece, Fabrizio
%A Kautz, Jan
%J JVRB - Journal of Virtual Reality and Broadcasting
%D 2013
%V 10(2013)
%N 2
%@ 1860-2037
%F pece2013
%X Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.
%L 004
%K Exposure Fusion
%K HDR
%K Motion Correction
%K Motion Detection
%K Time Varying Photography
%R 10.20385/1860-2037/10.2013.2
%U http://nbn-resolving.de/urn:nbn:de:0009-6-36506
%U http://dx.doi.org/10.20385/1860-2037/10.2013.2
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Bibtex

@Article{pece2013,
  author = 	"Pece, Fabrizio
		and Kautz, Jan",
  title = 	"Bitmap Movement Detection: HDR for Dynamic Scenes",
  journal = 	"JVRB - Journal of Virtual Reality and Broadcasting",
  year = 	"2013",
  volume = 	"10(2013)",
  number = 	"2",
  keywords = 	"Exposure Fusion; HDR; Motion Correction; Motion Detection; Time Varying Photography",
  abstract = 	"Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.",
  issn = 	"1860-2037",
  doi = 	"10.20385/1860-2037/10.2013.2",
  url = 	"http://nbn-resolving.de/urn:nbn:de:0009-6-36506"
}
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RIS

TY  - JOUR
AU  - Pece, Fabrizio
AU  - Kautz, Jan
PY  - 2013
DA  - 2013//
TI  - Bitmap Movement Detection: HDR for Dynamic Scenes
JO  - JVRB - Journal of Virtual Reality and Broadcasting
VL  - 10(2013)
IS  - 2
KW  - Exposure Fusion
KW  - HDR
KW  - Motion Correction
KW  - Motion Detection
KW  - Time Varying Photography
AB  - Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.
SN  - 1860-2037
UR  - http://nbn-resolving.de/urn:nbn:de:0009-6-36506
DO  - 10.20385/1860-2037/10.2013.2
ID  - pece2013
ER  -
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Wordbib

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<b:Comments>Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.</b:Comments>
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ISI

PT Journal
AU Pece, F
   Kautz, J
TI Bitmap Movement Detection: HDR for Dynamic Scenes
SO JVRB - Journal of Virtual Reality and Broadcasting
PY 2013
VL 10(2013)
IS 2
DI 10.20385/1860-2037/10.2013.2
DE Exposure Fusion; HDR; Motion Correction; Motion Detection; Time Varying Photography
AB Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.
ER
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Mods

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  </name>
  <abstract>Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.</abstract>
  <subject>
    <topic>Exposure Fusion</topic>
    <topic>HDR</topic>
    <topic>Motion Correction</topic>
    <topic>Motion Detection</topic>
    <topic>Time Varying Photography</topic>
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Full Metadata

Bibliographic Citation JVRB, 10(2013), no. 2.
Title

Bitmap Movement Detection: HDR for Dynamic Scenes (eng)
Author Fabrizio Pece, Jan Kautz
Language eng
Abstract Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.
Subject Exposure Fusion, HDR, Motion Correction, Motion Detection, Time Varying Photography
Classified Subjects
swd
  • 4790204-8, High Dynamic Range
  • 4006684-8, Bildverarbeitung
DDC 004
Rights DPPL
URN: urn:nbn:de:0009-6-36506
DOI https://doi.org/10.20385/1860-2037/10.2013.2