polarization-based dehazing

http://www.cg.info.hiroshima-cu.ac.jp/

Computer Graphics Laboratory, Hiroshima City University

Polarization-based dehazing using two reference objects

Daisuke Miyazaki Daisuke Akiyama

Masashi Baba Ryo Furukawa

Shinsaku Hiura Naoki Asada


CG Lab, Hiroshima City University

Ah... I’m scared of driving under hazy weather...

Hiroshima (Japan) has lots of fogs and yellow dusts...

Background

Introduction(1/3) Proposed method(7) Experiment(6) Discussion(2)



Input(Hazy image)

Output(Dehazed image)

Attenuationparameters

argminAttenuationparameters

Input Reference Input Reference

2 2

Overview

Introduction(2/3) Proposed method(7) Experiment(6) Discussion(2)


CG Lab, Hiroshima City UniversityIntroduction(3/3) Proposed method(7) Experiment(6) Discussion(2)

Related work

• Intensity-based– [Narasimhan, Nayar 2000]– [Tan 2008]– [Fattal 2008]– [He, Sun, Tang 2011]

• Polarization-based– [Schechner, Narasimhan, Nayar 2003]– [Schechner, Karpel 2005]– [Shwartz, Namer, Schechner 2006]– [Treibitz, Schechner 2009]

Our approach

(After parameter estimation [off-line process])

Haze can be removed in real-time

Theory is physics-based thus

reliable



Light is electro-magnetic wavePolarization = light oscillated non-uniformly

Unpolarized light

Perfect linear polarization

Polarization

Introduction(3) Proposed method(1/7) Experiment(6) Discussion(2)



Haze

Attenuated object lightT

Scattered light AObserved light I

TAI

Object light

Observed light

(Observed light) = (Scattered light) + (Attenuated object light)




Sun

Unpolarized

Scattering

Partiallypolarizedlight

Component parallel to scattering plane (superscript: )Component perpendicular to scattering plane (superscript: )

||

Polarization of scattered light




Observedlight

Haze

Distance

I

RCamera

Object light

Z

Attenuated object lightCamera

Object

T

Scattered light

A

Attenuation exp(-bZ)

Distance

Maximum scattered light

A

Lightsource

ZZ ReeAI

2

11||||

ZZ ReeAI

2

11

Formulation of observed light




Reference objects Captured image

Concept of parameter estimation




Observed light

Trafficsign 1

Haze

Distance

I

Z

R

Trafficsign 2

1p

2q1

2

Camera

Observed light

Object light

Distance

Trafficsign 1

Trafficsign 2

R

Z

I

1p

2q

Object light

Camera

Input:

Levenberg-Marquardt method

PP p

Zp

Zp eReAI

2

1||||

111

2

11

1

Qq

Zq

Zq eReAI

2

2||||

222

2

11

1

Q

2

1111

2

11 Z

pZ

p eReAI

2

2222

2

11 Z

qZ

q eReAI

,,

||

||

minarg,,

AA

AA

[Initial value]64||

AA

21

21 ZZ

for 8bit camera

21212||21

||1 ,,,,,,, RRZZIIII

Output: ,,|| AA

Parameter estimation from two references




¥A

[Schechner 2003] use sky region as A¥

Reason 1: Stratosphere is farReason 2: Universe is dark

If sky is unobserved...If mountain boundary undetected...

Related work




Light

Water tank

Polarization camera

Traffic sign1

Traffic sign 2

Black paint particle scatters the light

Experimental setup

Introduction(3) Proposed method(7) Experiment(1/6) Discussion(2)



Captured images

Realtimemonochromepolarizationcamera

Input Imax

(related to )I

Input Imin

(related to )||I




Degree of polarization

0

1

Degree of polarization




Two reference objects

3.47A

2.39|| A

169.0

Reference image

Estimatedparameters




OutputObject light R

OutputDepth Z

Output image




Image enhancement result

Input attenuated image Output ameliorated image




Sky area not concerned

Image enhanced atnot only reference objectsbut also other objects

Close objects failParticle distribution isn’t uniformParticle size isn’t sameWater tank size is finiteSpecular reflection of reference objectDark diffuse reflectionIllumination isn’t uniformClose distance from illuminationPolarization of water surfaceAffected by incident angle

Discussion

Introduction(3) Proposed method(7) Experiment(6) Discussion(1/2)



Color relatime polarization cameraSet camera on vehiclesTraffic sign recognitionOn-line parameter updationHigh precision using 3 or more traffic signsCreating traffic sign databaseCompute distance from traffic sign sizeIntrinsic camera calibration

Future work

Introduction(3) Proposed method(7) Experiment(6) Discussion(2/2)


Computer Graphics Laboratory, Hiroshima City University

(c) Daisuke Miyazaki 2013All rights reserved.

http://www.cg.info.hiroshima-cu.ac.jp/~miyazaki/Daisuke Miyazaki, Daisuke Akiyama, Masashi Baba, Ryo

Furukawa, Shinsaku Hiura, Naoki Asada, “Polarization-based dehazing using two reference objects,” CPCV, 2013.

polarization-based dehazing

Technology