Colour Theory Fundamentals

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Presentation transcript:

Colour Theory Fundamentals

Ways of looking at colour Physics Human visual receptors Subjective assessment

The physics of colour A pure colour is a wave with: Wavelength (λ) Amplitude (intensity or energy) (I)

Colours are energy distributions Lasers are light sources that contain a single wavelength (or a very narrow band of wavelengths) In practice light is made up of a mixture of many wavelengths with an energy distribution.

Light distribution for red

Sunlight

Human Colour Vision Human colour vision is based on three ‘cone’ cell types which respond to light energy in different bands of wavelength. The bands overlap in a curious manner.

Human receptor response

Tri-Stimulus Colour Theory The receptor performance implies that colours do not have a unique energy distribution And more importantly Colours which are a distribution over all wavelengths can be matched by mixing three R G B

Colour Matching Given any colour light source, regardless of the distribution of wavelengths that it contains, we can try to match it with a mixture of three light sources X = r R + g G + b B where R, G, and B are pure light sources and r, g, b their intensities For simplicity we can drop the R, G, B

Subtractive matching Not all colours can be matched with a given set of light sources (we shall see why later) However, we can add light to the colour we are trying to match: X + r = g + b With this technique all colours can be matched.

The CIE diagram The CIE diagram was devised as a standard normalised representation of colour. As we noted, given three light sources we can mix them to match any given colour, providing we allow ourselves subtractive matching. Suppose we normalise the ranges found to [0 ... 1] to avoid the negative signs.

Normalised colours Having normalised the range over which the matching is done we can now normalise the colours such that the three components sum to 1. Thus x = r/(r + g + b) y = g/(r + g + b) z = b/(r + g + b) = 1 – x – y We can now represent all our colours in a 2D space.

Defining the normalised CIE diagram

Actual Visible Colours

The CIE diagram 1964 standard

Convex shape Notice that the pure colours (coherent λ) are round the edge of the CIE diagram, The shape must be convex, since any blend (interpolation) of pure colours should create a colour in the visible region. The line joining purple and red has no pure equivalent. The colours can only be created by blending.

Intensities Since the colours are all normalised there is no representation of intensity. By changing the intensity perceptually different colours can be seen.

White point When the three colour components are equal, the colour is white: x = 0.33 y = 0.33 This point is clearly visible on the CIE diagram

Saturation Pure colours are called fully saturated. These correspond to the colours around the edge of the horseshoe. Saturation of an arbitrary point is the ratio of its distance to the white point over the distance of the white point to the edge.

Complement Colour The complement of a fully saturated colour is the point diametrically opposite through the white point A colour added to its complement gives us white.

Actual Visible Colours

Subtractive Primaries When printing colour, we use a subtractive representation. Inks absorb wavelengths from the incident light, hence they subtract components to create the colour. The subtractive primaries are Magenta (purple) Cyan (light blue) Yellow

Additive and Subtractive Primaries

Additive vs Subtractive Colour representation Surprisingly, the subtractive representation is capable of representing far more of the colour space than the additive. We will see why this is so shortly.

Colour Perception Perceptual tests suggest that humans can distinguish: 128 different hues For each hue around 30 different saturation. 60 and 100 different brightness levels. If we multiple these three numbers, we get approximately 350,000 different colours.

Colour Perception These figures must be treated with caution since there seems to be a much greater sensitivity to differentials in colour. Nevertheless, a representation with 24 bits (8bits for red, 8 bits for green and 8 bits for blue) does provide satisfactory results.

Reproducible colours Colour monitors are based on adding three the output of three different light emitting phosphors or diodes. The nominal position of these on the CIE diagram is given by: x y z Red 0.628 0.346 0.026 Green 0.268 0.588 0.144 Blue 0.150 0.07 0.780

Actual Visible Colours

RGB to CIE The monitor RGB representation is related to the CIE colours by the equation:

HSV Colour representation The RGB and CIE systems are practical representations, but do not relate to the way we perceive colours. For interactive image manipulation it is preferable to use the HSV (or SHI) representation. HSV has three values per colour: Hue – corresponds notionally to pure colour. Saturation – the proportion of pure colour. Value – the brightness (sometimes called Intensity (I))

Visualising the Perceptual Colour Space

Conversion between RGB and HSV V = max (r,g,b) S = (max(r,g,b) – min(r,g,b)) / max(r,g,b) Hue (which is an angle between 0 and 360o) is best described procedurally.

Calculating hue If (r=g=b) Hue is undefined, the colour is black, white or grey If (r>b) and (g>b) Hue = 120 * (g-b)/((r-b) + (g-b)) If (g>r) and (b>r) Hue = 120 + 120* (b-r)/((g-r) + (b- r)) If (r>g) and (b>g) Hue = 240 + 120 * (r-g)/((r-g) + (b-g))

Saturation in the RGB system In the RGB system, we can treat each point as a mixture of pure colour and white. Note, however that the so called pure colours are not coherent wavelengths as in the CIE diagram.

The composition of a tri-stimulus colour

Alpha Channels Colour representations in computer systems sometimes use four components – r g b  The fourth is simply an attenuation of the intensity which: Allows greater flexibility in representing colours. Avoids truncation errors at low intensity. Allows convenient masking certain parts of an image.

Perceptual Colour Space Hue

Perceptual Colour Space Saturation

HSV vs RGB

HSV: Increasing saturation for three value levels