TBD
- light source, object, (continuous) sensor
- also need an aperture or lens
- actual image is effectively continuous in space, time, and spectrum
- need to discretize each of those three with sampling
- pixels sample in space
- frames sample in time
What is Color?
- from physics, we know that the wavelength of a photon (typically measured in nanometers, or billionths of a meter) determines its apparent color
- we cannot see all wavelengths, but only the visible spectrum from around 380 to 750 nm
- but where are the following colors: “brown”, “pink”, “white”, …?
- clearly, the color spectrum does not actually contain all colors; i.e. some colors are non-spectral
- generally, a large number of photons with different wavelengths are simultaneosly impinging on any given location of your retina
- the actual incident light is not of a single wavelength, but can be described by a spectral histogram
- the histogram represents the relative quantity of photons of each wavelength
- the human eye cannot determine the exact histogram
- in fact just representing a complete spectral histogram exactly would require an infinite amount of space because it’s a continous quantity
- the biological solution is another form of sampling
- three types of cone cells respond (with the equivalent of a single number each) to the degree to which the actual incident histogram is similar to response histograms with peaks near red, green, and blue
- so the original continous histogram impinging on one location of your retina is reduced to three measurements
- (actually, there is a fourth rod cell type, which is mainly active in low light conditions)
- color blindness is typically caused by anomalies in the types of cone cells
- other animals also have different cone cells
- because we have again converted a continuous object into a set of discrete samples, we have to consider aliasing
- different incident histograms, called metamers, may be mapped to the same set of cone cell responses
- how many distinct colors can be seen?
- one way to think about it is to know that each cone cell type can distinguish between about 100 intensity levels of the associated response curve, and then to take a constructive approach
- there are
=1M ways to combine cone cell responses, so avg human can distinguish roughly that many colors
- the biology of human cone cells is the not only the reason we often use RGB to represent color; in fact, it defines color. Color is not an intrinsic property of light, but rather a result of the interaction between human cone cells and histograms of incident light.
Color Spaces
- we can make an abstract color space by assigning one color to each axis in a 3D Cartesian space
- the other vertices of the cube correspond to mixes of colors: “cyan”, “magenta”, “yellow”, “white”, and “black”
- sometimes RGB are considered “additive” colors because they form a basis for the color space relative to black
- CMY can similarly be considered “subtractive” colors because, effectively
- cyan+red = white
- magenta+green = white
- yellow+blue = white
- additive colors typically used when light is generated by an output device (e.g. CRT, LCD)
- subtractive colors typically used when printing on white paper
- sometimes RGB and CMY are considered distinct color spaces
- another common and useful color space is HSV
- hue: the basic color, or chromaticity
- saturation: how “deep” the color is (vs “pastel”)
- value: the brightness of the color
- HSV is again a 3 dimensional space, but it is typically considered to use cylindrical coordinates
- this is mainly a construction to decompose the three dimensional color space in a way that is more useful to human designers
- also often useful in machine vision algorithms, which simulate our theories of (aspects of) human vision
- can visualize HSV space as a “morph” of RGB space
- “stretch” the white and black vertices up and down
- “line up” the remaining six vertices along a common horizontal plane
- for HSV, put the white vertex back onto plane
(a variation, HSL, keeps white and black symetrically above and below
)
- hue is the radial angle “around” the cylinder
- saturation is the radial distance “out” from the center of the cylinder
- lightness is the “height” from the bottom to the top of the cylinder
- a common color picker uses the HSV model, with a rotating triangle inscribed inside a “hue circle”
- TBD RGB->HSV equations
