2.4 Color images & 2.5 Cameras

2.4 Color images

2.4.1 Physics of color



2.4.2 Color perceived by humans


XYZ color space
http://en.wikipedia.org/wiki/Xyz_color_space


color matching functions
: numerical description of the chromatic response of the observer

color gamut:
subsapce of colors perceived by humans

http://en.wikipedia.org/wiki/Gamut
Digitizing a photograph, converting a digitized image to a different color space, or outputting it to a given medium using a certain output device generally alters its gamut, in the sense that some of the colors in the original are lost in the process.

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2.4.3 Color spaces

http://en.wikipedia.org/wiki/Color_space

http://en.wikipedia.org/wiki/Rounding_error

(1) RGB color space
- CRT
- relative color standard
- additive color mixing
- sRGB, Adobe RGB, Adobe Wide Gamut RGB

http://en.wikipedia.org/wiki/RGB_color_space
The complete specification of an RGB color space also requires a white point chromaticity and a gamma correction curve.


(2) YIQ color space

- additive color mixing
- luminance (the perceived energy ot a light source)

http://en.wikipedia.org/wiki/YIQ
The Y component represents the luma information, and is the only component used by black-and-white television receivers. I and Q represent the chrominance information.

(3) YUV color space

http://en.wikipedia.org/wiki/YUV
Y' stands for the luma component (the brightness) and U and V are the chrominance (color) components.


(4) CMY color space
- subtractive color mixing (in printing process)
- sets of inks, substrates, and press characteristics

http://en.wikipedia.org/wiki/CMYK_color_model
masking certain colors on the typically white background (that is, absorbing particular wavelengths of light)


(5) HSV color space
- Hue, Saturation, Value (; HSB, Hue, Saturation, Brightness ; HSI; Hue, Saturation, Intensity)
- => image enhancement algorithms

http://en.wikipedia.org/wiki/HSL_and_HSV
Because HSL and HSV are simple transformations of device-dependent RGB, the color defined by a (h, s, l) or (h, s, v) triplet depends on the particular color of red, green, and blue “primaries” used. Each unique RGB device therefore has unique HSL and HSV spaces to accompany it. An (h, s, l) or (h, s, v) triplet can however become definite when it is tied to a particular RGB color space, such as sRGB.

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2.4.4 Palette images


palette images; indexed images

lookup table; color table; color map; index register; palette

The number of colors in the image exceeds the number of entries in the lookup table and a subset of colors has to be chosen, and a loss of information occurs.

http://en.wikipedia.org/wiki/Palette_(computing)

http://en.wikipedia.org/wiki/List_of_palettes

http://en.wikipedia.org/wiki/Indexed_color

vector quantization (-> 14.4)
1) to check which colors appear in the image by creating histograms for all three color components
2) to quantize them to provide more shades for colors which occur in the image frequently
3) to find the nearest color in the lookup table to represent the color 

=> to analyze large multi-dimensional datasets

http://en.wikipedia.org/wiki/Vector_quantization

http://en.wikipedia.org/wiki/Cluster_analysis
Clustering is the classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait - often proximity according to some defined distance measure.

http://en.wikipedia.org/wiki/K_means
The k-means algorithm is an algorithm to cluster n objects based on attributes into k partitions, k < n. It is similar to the expectation-maximization algorithm for mixtures of Gaussians in that they both attempt to find the centers of natural clusters in the data.


pseudocolor

Palette selection depends on the semantics of the image and is an interactive process.

2.4.5 Color constancy

The same surface color under diffrent illumination

 

von Kries coefficients
http://en.wikipedia.org/wiki/Color_vision

> color compensations

- to scale the sensitivity of each sensor type

=> automatic white balancing

- to assume that the brightest point in the image has the color of the illumination

 

2.5 Cameras: an overview

2.5.1 Photosensitive sensors

> photosensitive sensors in cameras
(1) photo-emission

photoelectric effect (; Hertz Effect)
http://en.wikipedia.org/wiki/Photoelectric_effect

photomultipliers
vacuum tube TV cameras

(2) photovoltanic

http://en.wikipedia.org/wiki/Solar_cell

photodiode
night vision camera
photoresistor
Schottky photodiode


> semiconductor photoresistive sensors
(1) CCDs (charge-coupled devices)
- arranged into a matrix-like grid of pixels (CCD chip)
- blooming effect
- shift registers
- SNR fropped

(2) CMOS (complementary metal oxide semiconductor)
- all of the pixel area devoted to light capture
- matrix-like sensors



2.5.2 A monochromatic camera

2.5.3 A color camera


2.6 Summary