Super-resolution of facial images in forensics scenarios

Publikation: Forskning - peer reviewKonferenceartikel i proceeding

Abstrakt

Forensics facial images are usually provided by
surveillance cameras and are therefore of poor quality and resolution.
Simple upsampling algorithms can not produce artifact-free
higher resolution images from such low-resolution (LR) images.
To deal with that, reconstruction-based super-resolution (SR)
algorithms might be used. But, the problem with these algorithms
is that they mostly require motion estimation between LR and
low-quality images which is not always practical. To deal with
this, we first simply interpolate the LR input images and then
perform motion estimation. The estimated motion parameters are
then used in a non-local mean-based SR algorithm to produce
a higher quality image. This image is further fused with the
interpolated version of the reference image via an alpha-blending
approach. The experimental results on benchmark datasets and
locally collected videos from surveillance cameras, show the outperformance of the proposed system over similar ones.
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Detaljer

Forensics facial images are usually provided by
surveillance cameras and are therefore of poor quality and resolution.
Simple upsampling algorithms can not produce artifact-free
higher resolution images from such low-resolution (LR) images.
To deal with that, reconstruction-based super-resolution (SR)
algorithms might be used. But, the problem with these algorithms
is that they mostly require motion estimation between LR and
low-quality images which is not always practical. To deal with
this, we first simply interpolate the LR input images and then
perform motion estimation. The estimated motion parameters are
then used in a non-local mean-based SR algorithm to produce
a higher quality image. This image is further fused with the
interpolated version of the reference image via an alpha-blending
approach. The experimental results on benchmark datasets and
locally collected videos from surveillance cameras, show the outperformance of the proposed system over similar ones.
OriginalsprogEngelsk
TitelIEEE 5th International Conference on Image Processing Theory, Tools and Applications
ForlagIEEE Signal Processing Society
Publikationsdato2015
Sider55-60
ISBN (Trykt)978-1-4799-8636-1, 978-1-4799-8637-8
DOI
StatusUdgivet - 2015
PublikationsartForskning
Peer reviewJa
BegivenhedIEEE International Conference on Image Processing Theory, Tools and Applications - Orleans, Frankrig
Varighed: 10 nov. 201513 nov. 2015
Konferencens nummer: 5th

Konference

KonferenceIEEE International Conference on Image Processing Theory, Tools and Applications
Nummer5th
LandFrankrig
ByOrleans
Periode10/11/201513/11/2015

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