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Color Harmonization
Daniel Coher-Or   Olga Sorkine       Ran Gal        Tommer Leyvand,   Ying-Qing Xu
                     Tel Aviv University, Microsoft Research Asia


                     A MXMLLN Montgomery Presentation




The                                                                    The
Great                                                                  Great
Wave                                                                   Wave
Off                                                                    Off
Kanagawa                                                               Kanagawa

Hokusai                                                                Hokusai
Introduction       Contributions   Results                        Critique


            Ou t lin e

  ●
   Introduction
      – Motivation
      – Previous Work
  •Contributions
      – Histogram Matching
      – Color Shifting
  ●
   Results
    ●
      Applications
    ●
      Limitations
  ●
   Critique




MXMLLN Montgomery                             University of Minnesota
Introduction           Contributions     Results                Critique

                    M o t iv a t io n ::C o lo r Ha r m o n y
   The authors define harmonic colors as sets of color that have some
   special order and relationship in color space resulting in a aesthetic
   visual appearance.




MXMLLN Montgomery                                      University of Minnesota
Introduction       Contributions       Results                 Critique

 P r e v io u s Wo r k


 Previous applications
 include mostly commercial
 design products that
 provide users with sets of
 harmonic colors

 None have the ability to
 harmonize an input image



     One solution attempts to automate part of the design process by
     introducing harmonic rules to assist the user. [MEIER, B.J 1988.
      ACE: a color expert system for user interface design.]
MXMLLN Montgomery                                     University of Minnesota
Introduction        Contributions      Results                 Critique

  P r e v io u s Wo r k
  The authors utilize Itten's color model where color harmony is defined
 as the relationships between hues on the color wheel. [Figure 2]


  In addition, the set of
  80 color schemes
  defined as
  combinations of the 8
  hue [Figure 2] and 10
  tone distributions that
  Matsuda produced
  from his
  psychophysical
  experiments are the
  foundation of this
  research.

MXMLLN Montgomery                                     University of Minnesota
Introduction     Contributions        Results                 Critique

     Im p le m e n t a t io n ::His t o g r a m M a t c h in g
  The main goal of Color Harmonization is to transform the color
  histogram of an image to match one of the eight hue distribution
  templates.




 ¿What makes the image disharmonious?
 ¿How would you traditionally determine the closest template?
 ¿Which template would you suggest?

MXMLLN Montgomery                                     University of Minnesota
Introduction     Contributions     Results                Critique

     Im p le m e n t a t io n ::His t o g r a m M a t c h in g




              Disharmonies
 The cyans, purples, and small amount
 of bright green are outliers in the
 predominantly dark blue and bright
 yellow and orange image.

      ¡There is no rainbow template!
MXMLLN Montgomery                                 University of Minnesota
Introduction       Contributions         Results                 Critique

     Im p le m e n t a t io n ::His t o g r a m M a t c h in g
 ●
   F(X, (m, a)) measures the harmony of the image X with respect to a
 scheme (m, a)
 ●
   M(X,Tm) defines the best harmonic scheme for the template Tm
 ●
   B(X) is the best harmonic scheme for the image X




           is the closest hue in the template Tm, oriented at angle a, to
 pixel p.
  H(p) is the hue channel
 S(p) is the saturation channel
 |·| is the arc distance on the hue wheel



MXMLLN Montgomery                                        University of Minnesota
Introduction      Contributions           Results                Critique

            Im p le m e n t a t io n ::C o lo r Sp lit t in g

  Color artifacts appear if a color from the
  hue histogram is halfway between the
  template borders             [Figure d]

  *Situation mostly arises when user inputs
  desired template




MXMLLN Montgomery                                        University of Minnesota
Introduction      Contributions             Results                Critique

            Im p le m e n t a t io n ::C o lo r Sp lit t in g

  Binary labeling segmentation using graph-cut optimization

  For each set of pixels Ω, minimize the energy E(V), the sum of the
  distance between the pixel hue H(p) and hue assignment H(v(p)),
  E1(V), and the grouping of adjacent pixels, E2(V)




                                       N is the set of neighboring pixels in Ω
                                       δ(v(p), v(q))) is 1 if labels of pixels
                                       p and q are diferent, else 0
                                       Smax(p,q) is the greater saturation
                                       between the two pixels

MXMLLN Montgomery                                          University of Minnesota
Introduction     Contributions         Results                Critique

            Im p le m e n t a t io n ::C o lo r Sh if t in g

  After pixels are assigned a region in the template, the hues are
  shifted to fit in the region

  Density of hues is preserved around hue at the center of the region
  C(p)

  Gσ(x) ε (0, 1] with standard deviation σ and mean 0




MXMLLN Montgomery                                     University of Minnesota
Introduction           Contributions        Results                 Critique

                    Re s u lt s ::In t e r [ f a c e , a c t io n ]




MXMLLN Montgomery                                           University of Minnesota
Introduction       Contributions        Results                 Critique

                    Re s u lt s ::A p p lic a t io n s

        The applications for Color Harmonization are extensive
        Anywhere digital design tools are used, there is a place for a
        color harmony recommendation system

                           Interior Design




MXMLLN Montgomery                                       University of Minnesota
Introduction        Contributions      Results                Critique

                      Re s u lt s ::A p p lic a t io n s


                           Graphic Design
                    Harmonize with respect to foreground
                    Harmonize with respect to background




MXMLLN Montgomery                                     University of Minnesota
Introduction         Contributions      Results                Critique

                       Re s u lt s ::A p p lic a t io n s


                            Graphic Design
                    Harmonize with respect to color scheme




MXMLLN Montgomery                                      University of Minnesota
Introduction     Contributions     Results                   Critique

                    Re s u lt s ::Dis c u s s io n
 Underlying algorithms give more weight to highly saturated pixels

 Unsaturated hues lead to less striking or noticeable results




MXMLLN Montgomery                                    University of Minnesota
Introduction      Contributions      Results                   Critique

                     Re s u lt s ::Lim it a t io n s

            No support for divided or interrupted hue regions




MXMLLN Montgomery                                      University of Minnesota
Introduction   Contributions        Results                Critique

                             C r it iq u e




MXMLLN Montgomery                                  University of Minnesota

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Color Harmonization

  • 1. Color Harmonization Daniel Coher-Or Olga Sorkine Ran Gal Tommer Leyvand, Ying-Qing Xu Tel Aviv University, Microsoft Research Asia A MXMLLN Montgomery Presentation The The Great Great Wave Wave Off Off Kanagawa Kanagawa Hokusai Hokusai
  • 2. Introduction Contributions Results Critique Ou t lin e ● Introduction – Motivation – Previous Work •Contributions – Histogram Matching – Color Shifting ● Results ● Applications ● Limitations ● Critique MXMLLN Montgomery University of Minnesota
  • 3. Introduction Contributions Results Critique M o t iv a t io n ::C o lo r Ha r m o n y The authors define harmonic colors as sets of color that have some special order and relationship in color space resulting in a aesthetic visual appearance. MXMLLN Montgomery University of Minnesota
  • 4. Introduction Contributions Results Critique P r e v io u s Wo r k Previous applications include mostly commercial design products that provide users with sets of harmonic colors None have the ability to harmonize an input image One solution attempts to automate part of the design process by introducing harmonic rules to assist the user. [MEIER, B.J 1988. ACE: a color expert system for user interface design.] MXMLLN Montgomery University of Minnesota
  • 5. Introduction Contributions Results Critique P r e v io u s Wo r k The authors utilize Itten's color model where color harmony is defined as the relationships between hues on the color wheel. [Figure 2] In addition, the set of 80 color schemes defined as combinations of the 8 hue [Figure 2] and 10 tone distributions that Matsuda produced from his psychophysical experiments are the foundation of this research. MXMLLN Montgomery University of Minnesota
  • 6. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g The main goal of Color Harmonization is to transform the color histogram of an image to match one of the eight hue distribution templates. ¿What makes the image disharmonious? ¿How would you traditionally determine the closest template? ¿Which template would you suggest? MXMLLN Montgomery University of Minnesota
  • 7. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g Disharmonies The cyans, purples, and small amount of bright green are outliers in the predominantly dark blue and bright yellow and orange image. ¡There is no rainbow template! MXMLLN Montgomery University of Minnesota
  • 8. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g ● F(X, (m, a)) measures the harmony of the image X with respect to a scheme (m, a) ● M(X,Tm) defines the best harmonic scheme for the template Tm ● B(X) is the best harmonic scheme for the image X is the closest hue in the template Tm, oriented at angle a, to pixel p. H(p) is the hue channel S(p) is the saturation channel |·| is the arc distance on the hue wheel MXMLLN Montgomery University of Minnesota
  • 9. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sp lit t in g Color artifacts appear if a color from the hue histogram is halfway between the template borders [Figure d] *Situation mostly arises when user inputs desired template MXMLLN Montgomery University of Minnesota
  • 10. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sp lit t in g Binary labeling segmentation using graph-cut optimization For each set of pixels Ω, minimize the energy E(V), the sum of the distance between the pixel hue H(p) and hue assignment H(v(p)), E1(V), and the grouping of adjacent pixels, E2(V) N is the set of neighboring pixels in Ω δ(v(p), v(q))) is 1 if labels of pixels p and q are diferent, else 0 Smax(p,q) is the greater saturation between the two pixels MXMLLN Montgomery University of Minnesota
  • 11. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sh if t in g After pixels are assigned a region in the template, the hues are shifted to fit in the region Density of hues is preserved around hue at the center of the region C(p) Gσ(x) ε (0, 1] with standard deviation σ and mean 0 MXMLLN Montgomery University of Minnesota
  • 12. Introduction Contributions Results Critique Re s u lt s ::In t e r [ f a c e , a c t io n ] MXMLLN Montgomery University of Minnesota
  • 13. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s The applications for Color Harmonization are extensive Anywhere digital design tools are used, there is a place for a color harmony recommendation system Interior Design MXMLLN Montgomery University of Minnesota
  • 14. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s Graphic Design Harmonize with respect to foreground Harmonize with respect to background MXMLLN Montgomery University of Minnesota
  • 15. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s Graphic Design Harmonize with respect to color scheme MXMLLN Montgomery University of Minnesota
  • 16. Introduction Contributions Results Critique Re s u lt s ::Dis c u s s io n Underlying algorithms give more weight to highly saturated pixels Unsaturated hues lead to less striking or noticeable results MXMLLN Montgomery University of Minnesota
  • 17. Introduction Contributions Results Critique Re s u lt s ::Lim it a t io n s No support for divided or interrupted hue regions MXMLLN Montgomery University of Minnesota
  • 18. Introduction Contributions Results Critique C r it iq u e MXMLLN Montgomery University of Minnesota