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Image Fusion
How to Best Utilize Dual Cameras
Corephotonics Proprietary Information
• UpdatedAdoptionRates:
30%in2018and50%in2019
• AllTopOEMsflagshipscontain
DualCameras
• NewlyreleasediPhone8&iPhoneX
containDualCameras
 DigiTimesResearch(July2017)
Source:CLSA,April2016
1584 1641 1516 1463
0
77 318 488
0%
4%
17%
25%
0%
5%
10%
15%
20%
25%
30%
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2015 2016CL 2017CL 2018CL
<Dual Cam Market Growth, CLSA, April , 2016 (Mil units)>
Smartphones without dual cam Smartphones with dual cam
Dual cam adoption (%)
Dual Camera Adoption  More Then Just a Trend
Dual-Camera Smartphone Market Growth
2Corephotonics Proprietary Information
Image Fusion - Overview
3
• Whatisit?
o ImageFusionistheprocessof
combiningtwoormoreinput
imagesintoasingleimage
• Whydoweneedit?
o Themainreasonforcombining
theimagesistogetamore
informativeoutputimage
Corephotonics Proprietary Information
Image Fusion – Example 1
4
• Mono+ColorDualCamera
o Themonochromaticsensorcaptures
2.5Xmorelight
ReachesbetterResolution&SNR
o Combinedoutputimagehasbetter
Resolution&SNR,especiallyin
lowlightconditions
Corephotonics Proprietary Information
Image Fusion – Example 2
5
• Wide+TeleDualCamera
o SimulatesacontinuousOpticalZoom
effect,asfoundinDSLRs
o Combinedoutputimagewillimprove
theResolution&SNRfromnoZoomup
tothepointtheTelephotoCamera’s
Field-of-Viewisthedominantone
Corephotonics Proprietary Information
Corephotonics Confidential | 6
Full FOV  Corephotonics Dual Camera Module
Corephotonics Proprietary Information
Corephotonics Confidential | 7
2X Digital Zoom
Corephotonics Proprietary Information
Corephotonics Confidential | 8
2X Fusion
Corephotonics Proprietary Information
Image Fusion – Algorithm Flow
9
• GenericschemeforFusion(Othermethodsexist)
• SomedifferencesbetweenWide + Tele & Color + Mono
Corephotonics Proprietary Information
Rectification
10
• Rectificationcorrectsfordistortion,scaleandshiftthatmaybeintroducedby
theOpticsandAFMechanism
• Thealgorithmusespre-computedrectificationdatathatisstoredinthe
sensors'OTPMemory
(FactoryCalibration)
• Output:Afterthisstep,correspondingpoints
inthetwoimageslieonEPI-Polarlines
Corephotonics Proprietary Information
Global Registration
11
• The algorithmcalculates and compensates forglobal
differencesbetweenthe 2 cameras which could be
attributedto dynamic changes between
images and specific properties
of eachcamera
Corephotonics Proprietary Information
Local Registration & Parallax Correction
12
• Fine Registration in which the parallax
(i.e.shiftinXandYdimensions,whichisbasedonobjectdistance)
is determined for each Pixel in the input images
Corephotonics Proprietary Information
Decision & Fusion
13
• Decision:
Handlesocclusions,correctsforRegistrationerrorsandhasan
adaptivealgorithmthateliminatesartifactsfromthefinalimage
• Fusion:
BlockthatimplementstheactualdataFusioninawaythatthe2
originalimagesareseamlesslyblendedtogether
X X
Corephotonics Proprietary Information
Image Fusion Challenges: Occlusions
14
• Howtobesthandleareaseach
cameraseesdifferently?
1. Inordertofusetwoimagesthe
algorithmneedstousematchingpixels
betweentheleftandrightimages
2. Incaseanareaisoccludedfromone
cameraamatchingpointcannotbe
detectedforthatarea
3. Handledbythedecisionblock
Corephotonics Proprietary Information
Image Fusion Challenges: Lens Imperfections
15
• ThedifferencesinDepthofField
areasthatcanbein-Focusinone
cameraandout-of-Focusinthe
2nd camera
• Registrationbecomesmuch
trickierbecauseofthedifficultyto
findfeaturepointsandmatching
Pixels
• TheDecisionBlockneedstoselect
thecamerathatisin-Focus
Corephotonics Proprietary Information
16
Wide Fused X1.5
Image Fusion Challenges: Lens Imperfections
Corephotonics Proprietary Information
Image Fusion Challenges: Overlap Transition
17
ThedifferenceintheField-of-ViewandtheResolutioncreates
aninevitableinclusionofoneimageinsidetheother
FusionwillnotcovertheentireField-of-Viewandthe
algorithmwillhavetoadjusttheFusion“Strength”graduallyto
allowanaturaluserexperienceinthetransitionareabetween
theimages.
Corephotonics Proprietary Information
Resolution
&
SNR Benefits
Corephotonics Proprietary Information
Apple iPhone 7+ Fusion FusionZoom Factor 1.8 with 570 Lux
• Tele & Wide images taken on iPhone
• Images processed by Corephotonics Image Fusion (Right) compared to iPhone Fusion (Left) Corephotonics Proprietary Information
FusionHuawei P10 Fusion
Corephotonics Proprietary Information
Mature & Artifact Free
User Experience
Corephotonics Proprietary Information
Show “thin lines” artifacts
Corephotonics Confidential |22
iPhone7+ creates Fusion Artifacts in such complex depth scenes
Apple iPhone 7+ Fusion FusionZoom Factor 1.8
Corephotonics Proprietary Information
What’s Next?
23
• OEMs push for higher Zoomfactor
Increasedneed for Image Fusion
• Verticalmarketapplications(AR / VR / MR)
o LowLightEnhancement
o Real-TimeFusion
• Largebaseline to accommodatedepth apps
Corephotonics Proprietary Information
Reference
24
To learnmore about Image Fusion
CorephotonicsImage Fusion WhitePaper
Corephotonics Proprietary Information
Thank You!
25
RoyFridman | DirectorofProductMarketing | rfridman@corephotonics.com
Corephotonics Proprietary Information

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Image Fusion - How to Best Utilize Dual Cameras

  • 1. Image Fusion How to Best Utilize Dual Cameras Corephotonics Proprietary Information
  • 2. • UpdatedAdoptionRates: 30%in2018and50%in2019 • AllTopOEMsflagshipscontain DualCameras • NewlyreleasediPhone8&iPhoneX containDualCameras  DigiTimesResearch(July2017) Source:CLSA,April2016 1584 1641 1516 1463 0 77 318 488 0% 4% 17% 25% 0% 5% 10% 15% 20% 25% 30% 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2015 2016CL 2017CL 2018CL <Dual Cam Market Growth, CLSA, April , 2016 (Mil units)> Smartphones without dual cam Smartphones with dual cam Dual cam adoption (%) Dual Camera Adoption  More Then Just a Trend Dual-Camera Smartphone Market Growth 2Corephotonics Proprietary Information
  • 3. Image Fusion - Overview 3 • Whatisit? o ImageFusionistheprocessof combiningtwoormoreinput imagesintoasingleimage • Whydoweneedit? o Themainreasonforcombining theimagesistogetamore informativeoutputimage Corephotonics Proprietary Information
  • 4. Image Fusion – Example 1 4 • Mono+ColorDualCamera o Themonochromaticsensorcaptures 2.5Xmorelight ReachesbetterResolution&SNR o Combinedoutputimagehasbetter Resolution&SNR,especiallyin lowlightconditions Corephotonics Proprietary Information
  • 5. Image Fusion – Example 2 5 • Wide+TeleDualCamera o SimulatesacontinuousOpticalZoom effect,asfoundinDSLRs o Combinedoutputimagewillimprove theResolution&SNRfromnoZoomup tothepointtheTelephotoCamera’s Field-of-Viewisthedominantone Corephotonics Proprietary Information
  • 6. Corephotonics Confidential | 6 Full FOV  Corephotonics Dual Camera Module Corephotonics Proprietary Information
  • 7. Corephotonics Confidential | 7 2X Digital Zoom Corephotonics Proprietary Information
  • 8. Corephotonics Confidential | 8 2X Fusion Corephotonics Proprietary Information
  • 9. Image Fusion – Algorithm Flow 9 • GenericschemeforFusion(Othermethodsexist) • SomedifferencesbetweenWide + Tele & Color + Mono Corephotonics Proprietary Information
  • 11. Global Registration 11 • The algorithmcalculates and compensates forglobal differencesbetweenthe 2 cameras which could be attributedto dynamic changes between images and specific properties of eachcamera Corephotonics Proprietary Information
  • 12. Local Registration & Parallax Correction 12 • Fine Registration in which the parallax (i.e.shiftinXandYdimensions,whichisbasedonobjectdistance) is determined for each Pixel in the input images Corephotonics Proprietary Information
  • 13. Decision & Fusion 13 • Decision: Handlesocclusions,correctsforRegistrationerrorsandhasan adaptivealgorithmthateliminatesartifactsfromthefinalimage • Fusion: BlockthatimplementstheactualdataFusioninawaythatthe2 originalimagesareseamlesslyblendedtogether X X Corephotonics Proprietary Information
  • 14. Image Fusion Challenges: Occlusions 14 • Howtobesthandleareaseach cameraseesdifferently? 1. Inordertofusetwoimagesthe algorithmneedstousematchingpixels betweentheleftandrightimages 2. Incaseanareaisoccludedfromone cameraamatchingpointcannotbe detectedforthatarea 3. Handledbythedecisionblock Corephotonics Proprietary Information
  • 15. Image Fusion Challenges: Lens Imperfections 15 • ThedifferencesinDepthofField areasthatcanbein-Focusinone cameraandout-of-Focusinthe 2nd camera • Registrationbecomesmuch trickierbecauseofthedifficultyto findfeaturepointsandmatching Pixels • TheDecisionBlockneedstoselect thecamerathatisin-Focus Corephotonics Proprietary Information
  • 16. 16 Wide Fused X1.5 Image Fusion Challenges: Lens Imperfections Corephotonics Proprietary Information
  • 17. Image Fusion Challenges: Overlap Transition 17 ThedifferenceintheField-of-ViewandtheResolutioncreates aninevitableinclusionofoneimageinsidetheother FusionwillnotcovertheentireField-of-Viewandthe algorithmwillhavetoadjusttheFusion“Strength”graduallyto allowanaturaluserexperienceinthetransitionareabetween theimages. Corephotonics Proprietary Information
  • 19. Apple iPhone 7+ Fusion FusionZoom Factor 1.8 with 570 Lux • Tele & Wide images taken on iPhone • Images processed by Corephotonics Image Fusion (Right) compared to iPhone Fusion (Left) Corephotonics Proprietary Information
  • 20. FusionHuawei P10 Fusion Corephotonics Proprietary Information
  • 21. Mature & Artifact Free User Experience Corephotonics Proprietary Information
  • 22. Show “thin lines” artifacts Corephotonics Confidential |22 iPhone7+ creates Fusion Artifacts in such complex depth scenes Apple iPhone 7+ Fusion FusionZoom Factor 1.8 Corephotonics Proprietary Information
  • 23. What’s Next? 23 • OEMs push for higher Zoomfactor Increasedneed for Image Fusion • Verticalmarketapplications(AR / VR / MR) o LowLightEnhancement o Real-TimeFusion • Largebaseline to accommodatedepth apps Corephotonics Proprietary Information
  • 24. Reference 24 To learnmore about Image Fusion CorephotonicsImage Fusion WhitePaper Corephotonics Proprietary Information
  • 25. Thank You! 25 RoyFridman | DirectorofProductMarketing | rfridman@corephotonics.com Corephotonics Proprietary Information