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C V L   S E M I N A R

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Wednesday, December 3, 11:00 AM

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Computer Vision Laboratory

Center for Automation Research

A.V. Williams Bldg., Room 4424

University of Maryland

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Biologically Inspired Enhancement of Dim Light Video

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Henrik Malm
Bio-inspired Image Analysis

Lund University, Sweden

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ABSTRACT

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 The inspiration for the video enhancement technique presented in this
talk lies in the spatiotemporal summation of intensities that enhances
vision in nocturnal animals. By applying an image analysis object called
the structure tensor, we analyze the intensity variation in the vicinity
of each pixel in the video data and find an optimal spatiotemporal
neighborhood within which intensities are averaged. In this way, noise
present in the dark image data (for example photon shot noise and
quantization errors) is effectively suppressed without creating
excessive edge and motion blur. We also sharpen the most important edges
for a more visually satisfying output. The technique will be described
in detail, and results of applying the method to an array of different
low light video sequences will be presented.


Biography: Henrik Malm


Henrik Malm is a researcher in Bio-inspired Image Analysis at Lund
University, Sweden. He received his MSc in Computer Science and
Technology in 1998 and his PhD in Applied Mathematics in 2003, focusing
on Computer Vision, both at Lund Institute of Technology. In the autumn
of 2000 he was a guest researcher at the Computer Vision Laboratory at
University of Maryland. He has been a post-doctoral fellow and
researcher at the Zoology Department at Lund University since 2004.

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For more information, contact Janice M. Perrone at (301) 405-1736 or
janice@umiacs.umd.edu

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<div class=3DSection1>

<p class=3DMsoNormal><o:p>&nbsp;</o:p></p>

<p class=3DMsoTitle>C V L&nbsp;&nbsp; S E M I N A R<span =
style=3D'font-size:10.0pt'><o:p></o:p></span></p>

<p class=3DMsoTitle><span =
style=3D'font-size:10.0pt'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><b><span
style=3D'font-size:14.0pt'>Wednesday, December 3, 11:00 =
AM<o:p></o:p></span></b></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><span
style=3D'font-size:20.0pt'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'>Computer =
Vision
Laboratory<o:p></o:p></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'>Center =
for Automation
Research<o:p></o:p></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><b>A.V. =
Williams
Bldg., Room 4424<o:p></o:p></b></p>

<p class=3DMsoNormal align=3Dcenter =
style=3D'text-align:center'>University of
Maryland<o:p></o:p></p>

<p class=3DMsoTitle><span =
style=3D'font-size:10.0pt'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoTitle><span =
style=3D'font-size:10.0pt'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter =
style=3D'text-align:center'><b>Biologically
Inspired Enhancement of Dim Light Video<o:p></o:p></b></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><b><span
style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></b></p>

<p class=3DMsoNormal align=3Dcenter =
style=3D'text-align:center'><b>Henrik Malm<br>
</b>Bio-inspired Image Analysis<o:p></o:p></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'>Lund =
University,
Sweden<span style=3D'font-family:"Times New =
Roman","serif"'><o:p></o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><span
style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><span
style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><span
style=3D'font-size:10.0pt;font-family:"Times New =
Roman","serif"'>ABSTRACT<o:p></o:p></span></p>

<p class=3DMsoNormal style=3D'text-align:justify'><span =
style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal =
style=3D'margin-bottom:12.0pt;text-align:justify'><span
style=3D'font-family:"Times New Roman","serif"'>&nbsp;</span>The =
inspiration for
the video enhancement technique presented in this talk lies in the
spatiotemporal summation of intensities that enhances vision in =
nocturnal
animals. By applying an image analysis object called the structure =
tensor, we
analyze the intensity variation in the vicinity of each pixel in the =
video data
and find an optimal spatiotemporal neighborhood within which intensities =
are
averaged. In this way, noise present in the dark image data (for example =
photon
shot noise and quantization errors) is effectively suppressed without =
creating
excessive edge and motion blur. We also sharpen the most important edges =
for a
more visually satisfying output. The technique will be described in =
detail, and
results of applying the method to an array of different low light video
sequences will be presented.<o:p></o:p></p>

<p class=3DMsoNormal =
style=3D'margin-bottom:12.0pt;text-align:justify'><br>
Biography: Henrik Malm<o:p></o:p></p>

<p class=3DMsoNormal =
style=3D'margin-bottom:12.0pt;text-align:justify'><br>
Henrik Malm is a researcher in Bio-inspired Image Analysis at Lund =
University,
Sweden. He received his MSc in Computer Science and Technology in 1998 =
and his
PhD in Applied Mathematics in 2003, focusing on Computer Vision, both at =
Lund
Institute of Technology. In the autumn of 2000 he was a guest researcher =
at the
Computer Vision Laboratory at University of Maryland. He has been a
post-doctoral fellow and researcher at the Zoology Department at Lund
University since 2004.<o:p></o:p></p>

<p class=3DMsoNormal style=3D'text-align:justify'><span =
style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal><span style=3D'font-family:"Times New =
Roman","serif"'><o:p>&nbsp;</o:p></span></p>

<p class=3DMsoNormal align=3Dcenter style=3D'text-align:center'><span
style=3D'font-size:10.0pt'>For more information, contact Janice M. =
Perrone at
(301) 405-1736 or janice@umiacs.umd.edu</span><span =
style=3D'font-size:26.0pt'><o:p></o:p></span></p>

<p class=3DMsoNormal><span =
style=3D'font-size:11.0pt;font-family:"Calibri","sans-serif"'><o:p>&nbsp;=
</o:p></span></p>

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