Practical aspects of HDR capture and acquisition (Deconstructing HDR) Francisco Imai
50
CREATE 2010 June 08 2010 Practical aspects of HDR capture and acquisition (Deconstructing HDR) Francisco Imai
description
Practical aspects of HDR capture and acquisition (Deconstructing HDR) Francisco Imai. CREATE 2010 June 08 2010. Disclaimer Only representing self Views in this presentations are not of any current or past employer. Image as representation. Real. Ideal. Tone editing. Ansel Adams. - PowerPoint PPT Presentation
Transcript of Practical aspects of HDR capture and acquisition (Deconstructing HDR) Francisco Imai
CREATE 2010
June 08 2010
CREATE 2010
June 08 2010
Practical aspects of HDR capture and acquisition(Deconstructing HDR)
Francisco Imai
Practical aspects of HDR capture and acquisition(Deconstructing HDR)
Francisco Imai
Disclaimer
Only representing selfViews in this presentations are not of
any current or past employer
Image as representation
Ideal Real
Tone editing
Ansel Adams
What about color HDR?
Merced River and El Capitan in Winter, Yosemite Valley [in Nature]
Image manipulation
Definition Dynamic Range
maximum non-saturated signal
DR = ------------------------------- minimum signal
Sensor technologies
www.pixim.com
HDR sensor technology:1. Multiple gains sensor
from Boyd Fowler [HDRI workshop 2009]
Advantages:
Good low light performanceGood linearity
Drawbacks:
Limited DR extensionAdditional silicon areaAdditional power dissipation
e.g. Dual column Level amp and ADC [Fowler 09], LOFIC [Adachi 05]
HDR capture technology:2. Non-linear pixel response sensor
from Boyd Fowler [HDRI workshop 2009]
Advantages: Wide DR > 120 dBInstantaneous measurementHigh fill factorSimple operation
Drawbacks:
No low-light videoLarger FPNDifferent sensor architectureNo solution for color sensors
e.g. Logarithmic sensor [Dierickx 95], Dynamic well capacity adjustment [Sayag 91, Decker 98]
HDR capture technology:3. Well-capacity recycling sensor
from Boyd Fowler [HDRI workshop 2009]
Advantages: Good linearityGood color imagingLarge DR > 100 dBBest SNR
Drawbacks:
Large pixel sizePoor low light performanceHigh power dissipationNeeds high speed read-out
e.g. Sigma delta pixel level ADC [Fowler 94], Asynchronous self-reset with multiple capture [Liu 02]
HDR capture technology:4. Time to saturation sensor
from Boyd Fowler [HDRI workshop 2009]
Advantages: Very HDR > 150 dB
Drawbacks:
High power dissipationLarge pixel
e.g. Time to saturation [Brajovic 96]
HDR capture technology:5. Time varying exposures
Advantages: Use conventional sensors
Drawbacks:
Motion blur
e.g. Two sample CID [Nakamura 97], Two sample APS [Yadid-Peckt 97]
Blended exposures
HDR capture technology:6. Spatially varying exposures
from Boyd Fowler [HDRI workshop 2009] and www.pixim.com
Advantages: Excellent linearityColor ImagingDR > 100 dB
Drawbacks:
High power dissipationLarge pixelPoor low light performanceNeeds high speed read-out
e.g. DPS pixel [Yang 99], Fuji Super CCD
Pixim DPS
There are plenty of publication on HDR imaging sensors but
most of cameras still do not use them.
WHY?
Example
20 f-stops in HD-video
Spherican 180-360 degrees26 f-stops, 50 Mpixel
20 s to 1 minute
Example
F200 EXR, F70EXR, F80EXR and S200 EXR
FujiFim SuperCCD EXR
What to do with captured HDRI?
-Tone map to display in conventional displays-Global tone mapping-Local tone mapping-iCAM-Retinex
-Build an HDR display
25
SIGGRAPH 2005 - Seetzen et al.
14 bits
1300 cd/m2
Off-the-shelf components HDR display
26
HDR display modeling
27
HDR display forward model
• All possible sextuplets combination is 6256 = 281 trillion
• Inaccurate colorimetric measurement in dark region (resulting in green cast in dark areas when model is used)
• Problem with cross-terms between LCD and DLP
• More robust physical based model is necessary
28
Radiance based Forward model
Decompose 12 Component XYZ and perform
a priori eigenvector analysis
29
LCD display spectral radiance
Red, green and blue ramps
30
LCD additivity
Comparison sum of red, green and blue Channels with gray measurements
31
Spectral radiance measurements
Photo Research PR-650
32
Spectral radiance measurement
DLP light reflected on MgO2
Measurement Red, Green, Blue Ramps
Close-up measured areafor green ramp
33
Additivity DLP channels?White is not active White is active
White channel
34
DLP Radiance
LCD Radiance
Transmittance LCD
Transmittance LCDTransmittance LCD
35
Compare LCD radiance between measurement and estimation
usingforward model
Blue Green Red
36
Comparison measured and estimated LCD radiance
37
Estimation Final RadianceTraining set
38
luminance x chroma Hue angle x chroma
Verification 100 “random” samples (20 samples with white
on white on DLP)
39
Inverse HDR model
40
Colorimetric performance100 Random Samples
41
Extra Verification set (280 samples)
Neutral ramp (14 levels)4 octaves of Color Checker
170 objects (Vrhel)
Mean CIEDE2000 = 2.4Maximum CIDE2000 = 7.7
Excluding 7 outliers (out-of-gamut samples)
42
HDR rendering accuracy assessment
Veiling glare
Scene-dependent scatter in optics/camera and in the human eye
reduce the HDR
TalvalaSIGGRPAH 2007
Other IQ aspect: SNRfrom Boyd Fowler [HDRI workshop 2009]
Other IQ aspect: Resolution
Quick MTF
Other IQ aspect: Colour
EyeRex – SW by Media Chance
Evocative HDR look
Fantoft stavkirke –www.pappafrezzo.com
Nina Aldin Thune
Tunliweb
Hype Cycle HDRI
Acknowledgments
Unanswered questions
1. When are we going to have HDR cameras on cell-phone cameras?
2. How to deal with white balance in HDR?
3. What set of metrics is appropriate for HDR display quality?
