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Dealing with the Complexities of Camera ISP Tuning
Clément Viard, Sr Director, R&DFrédéric Guichard, CTO, [email protected]
1© DxO Labs 2016 | PREPARED FOR: AutoSens conference
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Dealing with the Complexities of Camera ISP Tuning
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> Basic camera image processing
> First revolution: optical and sensor defects corrections
> Second revolution: miniaturization
> ISP, A key differentiator in image and video processing
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Introduction
« Basic » digital image processing in a camera
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RAW data from Sensor
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After « demosaicing »
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After exposure adaptation
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After « white ballance »
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After color rendering
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After sharpening
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A digital revolution in cameras
Optical and sensor defect corrections
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Geometric distortion
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Geometric distortion
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Volume anamorphos – perspective error with wide angle lenses
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Volume anamorphos – perspective error with wide angle lenses
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Optical vignetting
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Chromatic aberation
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Chromatic aberation
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Tone mapping
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Tone mapping
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Tone mapping (with HDR sensor)
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Tone mapping (with HDR sensor)
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Clipping – Recovering saturated area
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Clipping – Recovering saturated area
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Roll
Yaw
Pitch
X
Y
Z
Stabilisation and Electronic Rolling Shutter (ERS) effect
Translation Z
Yaw (Rotation)
Translation X
Pitch (Rotation)
Translation Y
ERS horizontal
ERS vertical
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Range of Digital Corrections with Advanced ISPs
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> Optical aberrations> Distortion> Blur (spherical aberration, field
curvature, coma, astigmatism, motion)> Chromatic aberrations> Vignetting> Flare, veiling glare
> Light & Sensor> Noise> Dynamic range> Contrast> Atmospheric haze
> Sensor limitations> Field non uniformity (color, black
level,…)> Defective pixels, Dust> Clipping> Metamerism
> Others> Video stabilization> Electronic rolling shutter
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Miniaturization – the second camera revolution
Will they eventually reach same performance?
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Sensor Miniaturization Challenge
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22 times less light 4.5 stops
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Performance improvement over 10 years
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> CMOS Sensor improvement : +1.5 stops
> Digital processing gain: +3 to +4 stops
DxOMark sensor score, APS-C cameras
+1.5 stops
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Nikon D70s, ISO 3200 – jpg
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Nikon D70s, ISO 3200 – RAW + DxO Optics Pro v3
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Nikon D70s, ISO 3200 – RAW + DxO Optics Pro v7
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Nikon D70s, ISO 3200 – RAW + DxO Optics Pro v9
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Nikon D70s, ISO 3200 – RAW + DxO Optics Pro v11
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Nikon D70s, ISO 3200 – jpg
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Sensor color response changes with CRA
Photosite
Color response as a function of the angles350 450 550 650 750
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ISP
A key differentiator in image and video processing
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« ISP » as a key differentiator
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> Enables camera hardware and scene artefact corrections
> Only remaining differentiator since access to best sensor and lens is now ubiquitous
> Paradigm shift, cameras are designed considering possible digital corrections
> Computing power requirement consistently increasesDelivering 2,000 Ops/pixel with 240 Mpix/s (24 frames at 10Mpix per second) requires 500 GOps/s
> Very significant investment within the Mobile industry(e.g. iPhone camera engineering team ~ 800 people)
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Same HW, same ISP, same BOM same image quality?
DxO Mark Mobile score (Photos and Videos)38© DxO Labs 2016 | PREPARED FOR: AutoSens conference
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« Camera Tuning »
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For correcting each image, ISP requires 10,000+ register settings to be adapted to the situation.
> Per serie Calibration
> Per unit Calibration
> On the fly parameter estimations
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Image Quality Evaluation Challenge
> What is “Image Quality”?> Perception of how a picture “looks good”> In essence a subjective matter…that can be modeled with engineering tools
> What influences “Image Quality”> Shooting conditions: illumination, illuminant, dynamic> Content has a strong influence on Image Quality perception and image processing> Image Quality perception is different between imaging expert, professional
photographers and consumer
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Image Quality Evaluation Challenge - Subjective vs. objective
> Objective evaluation> Objective means a measurement that is neutral, operator independent: “2
cm, 15 meters, 150 kg, 2 g, -5°C, 50°C, …”> A device must provide figures (metrics) that are related to image quality> Normalizations may be necessary to have comparable metrics (cameras
with different resolutions)> Only addresses a set of metrics (some artifacts may be ignored)
> Subjective evaluation> “Subjective” means real people give an opinion like: “big, small, heavy, light,
cold, hot, …”> People can judge the quality of photographs> Methodology is key to get non-biased results
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Camera IQ assessments
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Temporal behaviorDynamic behavior Photogrammetry and 3D
Thousands of videos/photos are required to characterize IQ along differentdimensions
Specifying AND verifying image quality targets are tough challenges
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Just Noticeable Difference (JND), a Matter of Statistics
> The smallest statistically measurable difference of perception, e.g., smallest perceivable distance between 2 parallel lines
> Typically, defined when half of the people perceive a difference and the other half are guessing (50% JND)
50% perceive
a change 50% guessing
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Anchored Scaling Concept
C D E F
Test image
??
Anchors
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Objective/subjective correlation example: Sharpness JND mapping
After extensive visual experiments, one could show that the Acutance objective metric linearly correlates with perception of sharpness (expressed with JND unit)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
5
10
15
20
25
30
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Acutance
JN
D
0
20
40
60
80
100
120
0.0 0.1 0.2 0.3 0.4 0.5
MTF
(%
)
Frequency (cycle/pixel)
CSF
MTF
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Back to the real world!
> Unfortunately the assumptions to build a complete multi-variate analysis based scoring system are not met > Only few metrics are linearly correlated to perception> They are not strictly orthogonal to each others> New issues comes with every technological improvement
> Since we can’t build a unified scoring system based on a set of perceptual metrics, a Multi-Modal approach is required
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Recommendation for building a relevant Image or video score
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> Multi-modal testing approach> Objective measurements in lab environment> Perceptually-correlated metrics when available> Perceptual analysis from natural scenes
> Multi-level testing results> Overall, Photo, and Video scores> Top-level scores (open scale) non technical> Detailed reports for engineering
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Example of natural scene set used for mobile camera application
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Conclusion
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> Eventually, all industries would benefit from Smartphone technology breakthroughs
> ISP can fix many optical and sensor defects
> ISP technology improvements are a key enabler for miniaturization
> Mastering tuning complexity and IQ evaluation is a key differentiator
> DxO has developed robust methods to deal with this problem
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1 / DxO USA 1407 Minnesota Street San Francisco, CA [email protected]: +1 415 805 8567
2 / DxO France3, rue Nationale 92100 Boulogne-Billancourt France [email protected] Tel: +33 1 55 20 55 99
3 / DxO Korea16th Floor, Gangnam Building 1321-1 Seocho-dong, Seocho gu Seoul [email protected]: +82 2 2190 3825
4 / DxO TaiwanTai Centre 2/F-A170 Dunhua North Road Taipei 10548Taiwan Tel: +886 2 5574 0429
5 / DxO Japan3F Metlife Kabutocho Bldg 5-1 Kabutocho Chuo-ku Nihonbashi, [email protected]: +81 (0)3 6861 7565
Thank you!
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