Color Constancy from Illumination Changes

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(MIRU2004) 2004 7 153-8505 4-6-1 E E-mail: {rei,robby,ki}@cvl.iis.u-tokyo.ac.jp Finlayson [10] Color Constancy from Illumination Changes Rei KAWAKAMI,RobbyT.TAN, and Katsushi IKEUCHI Institute of Industrial Science, University of Tokyo 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, JAPAN E-mail: {rei,robby,ki}@cvl.iis.u-tokyo.ac.jp Abstract Elimination of illumination color in color images is essential for various fields in computer vision. Many methods have been proposed to solve it, however there are few methods employing varying illumination as a constraint. We found Finlayson et al. s method [10] applicable for natural images, and extended it by making the reference illumination variable. To evaluate our method, we have conducted a number of experiments with natural images and also with textured images mapped on 3D data. The evaluation shows that the method has higher accuracy and robustness compared to the previous method. Key words color, color constancy, varying illumination, Planckian locus, texture 1. SPD(Spectral Power Distribution) Color constancy Color constancy [3], [5], [6], [9], [11] [16], [19] [24] Dichromatic based Diffuse based Dichromatic based [5], [9], [12] [14], [19], [20], [22] Diffuse based [3], [6], [11], [21], [23], [24] Diffuse-based [11], [21], [23], [24] [2], [4], [10]

D zmura [4] Finlayson [10] Barnard [2] Retinex Algorithm [18] Finlayson Finlayson [10] Finlayson 2. 2. 1 I c (1) I c = S(λ)E(λ)q c(λ)dλ (1) Ω S(λ) E(λ) q c c (R,G,B) (Ω) Dirac (1) (2) 2. 2 (Planckian locus) ( ) Planckian locus Planckian locus [12], [17] Planckian locus RGB SPD(Spectral Power Distribution) Planck ( (6)) M(λ) =c 1λ 5 [exp(c 2/λT) 1] 1 (6) c 1,c 2 3.7418 10 16 (Wm 2 ), 1.4388 10 2 (mk), λ (m) T (K). (7) SPD RGB I c = M(λ, T )q c(λ)dλ (7) Ω Planckian locus I c = S ce c (2) [1], [7], [8] RGB RGB (3) 1 Planckian locus σ c = Ic I B (3) c R,G (2) σ c (4) σ c = s ce c (4) s c,e c S c,e c (4) (5) σc,σ 1 c 2 e 1,e 2 [ ] [ ][ σr 2 e 2 r/e 1 r 0 = σg 2 0 e 2 g/e 1 g σ 1 r σ 1 g ] (5) 2. 3 Finlayson [10] Finlayson [10] Finlayson 3. e ref e ref Φ Φ (8) [ ] e ref r /r 0 Φ (8) 0 e ref g /g ( (5)) Planckian locus (1/r, 1/g) 2

2 Planckian locus 3. Finlayson 5 σ 1 σ 2 Φσ 1 Φσ 2 3 Judd Daylight Phases CIE Finlayson Judd Daylight Phases(D48,D55,D65,D75,D100) CIE (A,B,C) ( 3 [17]) Planckian locus Planckian locus 1/r 1/g Φ σ Φσ σ 1,σ 2 Φσ 1,Φσ 2 (r, g) =(e 1 r,e 1 g) (e 2 r,e 2 g) σ ref σ ref (9) (0,0) 5 Planckian locus ( (8) e ref ) 3. 1 Finlayson s σ 1 σ 2 ( 6) Φσ 1 Φσ 2 = σ ref (9) 4 6 4 s s Planckian locus Planckian locus ( 1) Planckian locus e r,e g s s r,s g (4) σ r,σ g σ 1,σ 2 ( 7 Ex.3,Ex.4) s

7 3. 2 σ real σ real σ real 8 Finlayson s 8 s 1. 2. 3. 1. 2. s 3. g 1 g g 3. 3 (σ 1 σ 2 ) (σ ref ) σ 1 σ ref σ 2 ( (8) e ref ) se ref 6 7 7 Ex.1 Ex.2 7 Ex.3 Ex.4 4. 4. 1 RGB e ref 90 e ref (90 ) g g δ err Planckian locus 100(k) 0.01 CIE 0.2 [25] 4. 2 3CCD SONY DXC- 9000 Photo Research PR-650 (Photo Research Reflectance Standard model SRS-3) 4. 3 9 Finlayson 15:00 18:00( )

9 Finlayson 12 1 10 1 13 2 1 ( ) r g b r g b 1 0.235 0.265 0.500 0.245 0.281 0.474 2 0.316 0.306 0.377 0.293 0.292 0.415 11 2 9.a 9.b 9.c 9.d 9.e Finlayson Finlayson Finlayson [25]. 10 11 18:00( ) 12 13, 14 RGB 15 4. 4 ( + ) CIE (σ c = I c/σi i) 0.063 Finlayson 0.11 0.16 Finlayson 0.32 R B G Finlayson G 1 (CIE )

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