at td automated ptipreservationbecker/slides/20111026-icadl... · 2011. 11. 28. · dng by digikam....
TRANSCRIPT
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A t t d P tiAutomated Preservation:The Case of Digital Raw Photographs
Stephan Bauer, Christoph BeckerICADL 2011Beijingj g
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Joseph Nicéphore Niépce
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stallio (flickr)
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Why RAW
digital negativedigital negative
most authentic version of the image
no lossy compression as in jpeg
new tools may create better interpretationsy p
not an image: uninterpolated sensor data
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Developing a raw file
Demosaiquing
White balance adjustmentWhite balance adjustment
Colorimetric interpretationColorimetric interpretation
iTone mapping
Image enhancements
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interpretation
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Adobe
ron
vert
er
dcraw
e D
NG
CAdo
b
Applepp
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validate
migrate
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Evaluation framework
numerous proprietary raw formats – high risknumerous proprietary raw formats high risk
normalization to standardized format desirable
How to evaluate and validate?
preservation planningpreservation planningsystematic evaluation method and tool
controlled experimentationcontrolled experimentation
automated measurements
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migrate
comparison
comparison
comparison
comparison
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Automated Measurements
traditional quality assurance methods traditional quality assurance methods are error based
common tools not reliablecommon tools not reliable
requirementsperception based
respecting ICC-profiles
meaningful for color images
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equal MSE
https://ece.uwaterloo.ca/~z70wang/research/ssim/#MAD
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Significant Properties - Content
relative AESSIM
SSIM Hue
relative MSE
SSIM Saturation
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Significant Properties - Context
Exif (exposure)IPTC
Exif (technical)Dublin Core
MetadataExif (location)Private Tags
XMPExif (generated)(g )
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Contribution
image comparison metrics implementedimage comparison metrics implementedusing Java Advanced Imaging API
metadata e ification sing E ifToolmetadata verification using ExifTool
comparing Adobe DNGConverter and digiKamp g g
migrate and validate a representative selection
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Results – CRW
RAW DNG by digikam
raw data are identicalraw data are identicalincorrect color matrix generated
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Results – CRW
RAWRAW
DNG by digiKam
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Results – CR2
RAW DNG RAW DNG by
ADC
two embedded color matrices
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Results – CR2
RAW
DNG by ADC
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Conclusion
demonstrated fully automated QAi t t f th t t l l l th dusing state of the art perceptual level method
well suited to falsify: find bad conversionsyet not suited to fully verify conversions
SSIM allows meaningful measurements
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Outlook
implement workflows using tavernaimplement workflows using taverna
run large scale tests
correlation of SSIM and manual evaluation
use more tools for QAQ
expand approach to different types of content
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??Automated Preservation: The Case of Digital Raw PhotographsStephan Bauer, Christoph Becker, ICADL 2011
www.ifs.tuwien.ac.at/~becker