Polarization-based dehazing using two reference objects

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Presentation transcript:

Polarization-based dehazing using two reference objects Daisuke Miyazaki Daisuke Akiyama Masashi Baba Ryo Furukawa Shinsaku Hiura Naoki Asada

Background Ah... I’m scared of driving under hazy weather... Introduction(1/3) Proposed method(7) Experiment(6) Discussion(2) Ah... I’m scared of driving under hazy weather... Hiroshima (Japan) has lots of fogs and yellow dusts... Background

Overview 2 2 Attenuation parameters argmin Input (Hazy image) Output Introduction(2/3) Proposed method(7) Experiment(6) Discussion(2) 2 2 Attenuation parameters argmin Attenuation parameters Input Reference Input Reference Input (Hazy image) Output (Dehazed image) Overview

Related work Intensity-based Polarization-based Our approach Introduction(3/3) Proposed method(7) Our approach Experiment(6) Discussion(2) 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] (After parameter estimation [off-line process]) Haze can be removed in real-time Theory is physics-based thus reliable Related work

Polarization Light is electro-magnetic wave Introduction(3) Proposed method(1/7) Experiment(6) Discussion(2) Light is electro-magnetic wave Polarization = light oscillated non-uniformly Unpolarized light Perfect linear polarization Polarization

Observed light Observed light Scattered light Object light Introduction(3) Proposed method(2/7) Experiment(6) Discussion(2) Scattered light Observed light Object light Attenuated object light Haze (Observed light) = (Scattered light) + (Attenuated object light) Observed light

Polarization of scattered light Introduction(3) Proposed method(3/7) Experiment(6) Discussion(2) Sun Unpolarized Scattering Partially polarized light Component parallel to scattering plane (superscript: ) Component perpendicular to scattering plane (superscript: ) Polarization of scattered light

Formulation of observed light Introduction(3) Proposed method(4/7) Experiment(6) Discussion(2) Light source Haze Maximum scattered light A  Distance  Scattered light A Observed light Camera Attenuated object light T I Attenuation exp(-bZ) Object Distance Z Object light R Camera Formulation of observed light

Concept of parameter estimation Introduction(3) Proposed method(5/7) Experiment(6) Discussion(2) Reference objects Captured image Concept of parameter estimation

Parameter estimation from two references Introduction(3) Proposed method(6/7) Experiment(6) Discussion(2) Input: Haze Observed light I Output: 1p Traffic sign 1 Traffic sign 2 Camera Observed light Distance Z 1 I 2q Distance Z 2 Object light R 1p Traffic sign 1 Traffic sign 2 Camera Levenberg-Marquardt method Object light for 8bit camera R [Initial value] 2q Parameter estimation from two references

A Related work [Schechner 2003] use sky region as A¥ ¥ Introduction(3) Proposed method(7/7) Experiment(6) Discussion(2) [Schechner 2003] use sky region as A¥ ¥ A Reason 1: Stratosphere is far Reason 2: Universe is dark If sky is unobserved... If mountain boundary undetected... Related work

Experimental setup Light Traffic sign 2 Water tank Traffic sign1 Introduction(3) Proposed method(7) Experiment(1/6) Discussion(2) Light Traffic sign 2 Water tank Traffic sign1 Polarization camera Black paint particle scatters the light Experimental setup

Captured images Realtime monochrome polarization camera Input Imax Introduction(3) Proposed method(7) Experiment(2/6) Discussion(2) Realtime monochrome polarization camera Input Imax (related to ) Input Imin (related to ) Captured images

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

Two reference objects Reference image Estimated parameters Introduction(3) Proposed method(7) Experiment(4/6) Discussion(2) Reference image Estimated parameters Two reference objects

Output image Output Object light R Output Depth Z Introduction(3) Proposed method(7) Experiment(5/6) Discussion(2) Output Object light R Output Depth Z Output image

Image enhancement result Introduction(3) Proposed method(7) Experiment(6/6) Discussion(2) Input attenuated image Output ameliorated image Image enhancement result

Discussion Sky area not concerned Image enhanced at Introduction(3) Proposed method(7) Experiment(6) Discussion(1/2) Sky area not concerned Image enhanced at not only reference objects but also other objects Close objects fail Particle distribution isn’t uniform Particle size isn’t same Water tank size is finite Specular reflection of reference object Dark diffuse reflection Illumination isn’t uniform Close distance from illumination Polarization of water surface Affected by incident angle Discussion

Future work Color relatime polarization camera Set camera on vehicles Introduction(3) Proposed method(7) Experiment(6) Discussion(2/2) Color relatime polarization camera Set camera on vehicles Traffic sign recognition On-line parameter updation High precision using 3 or more traffic signs Creating traffic sign database Compute distance from traffic sign size Intrinsic camera calibration Future work

(c) Daisuke Miyazaki 2013 All 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.