Colour Constancy T.W. Hung

Colour Constancy – Human A mechanism enables human to perceive constant colour of a surface over a wide range of lighting conditions. Land studied and attempted to explain the mechanism, Retinex theory.

Colour Histogram 1 (picture 3) Image under reference lighting condition Colour Histogram 2 (picture 4) Image under biased lighting condition

Colour Constancy - Machine Problem: Model What form of a transform used in the algorithm is sufficient to discount the effect of change of illuminant Mechanism How to compute the parameters of the desired transformation

Common Assumption A set of squared colour patches Reasonable number of different coloured patches Surface property is Lambertian Single source of illumination Even illumination over the scene

Model Coefficient Model [Von Kries, Finlayson] C i,j,1 = T C i,j,2

Mechanism White patch algorithm Maximum to predefined maximum Grey world algorithm Average to predefined average Gamut mapping method Feasible mapping with Surface colour constraints, illumination constraints Specular highlight detection method Detect the presence of the specular highlight Retinex algorithm Average of logorithmic ratio of surface i and its neighborhood colours

“All objects that are known to us from experience, or that we regard as familiar by their colour, we see through the spectacles of memory colour” Hering 1878

Problem To compute a transformation to match the colours in the image to a database of ‘known’ colours. 1.Form of transformation 2.Fitness measure for the matching criteria 3.Matching method

Mahanobis eqn.

Experimental setting

Graph of lighting

Picture

Conclusion Description of the colour constancy problem: model and mechanism Description of some of the existing algorithms Simple linear transformation Minimum error matching criteria Match to ‘normalised’ colour model Adaptation to relative colour match, seems robust