Color in image and video Mr.Nael Aburas. outline  Color Science  Color Models in Images  Color Models in Video.

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Presentation transcript:

Color in image and video Mr.Nael Aburas

outline  Color Science  Color Models in Images  Color Models in Video

Color Science  Light and Spectra  Light is an electromagnetic wave. Its color is characterized by the wavelength content of the light.  Laser light consists of a single wavelength: e.g., a ruby laser produces a bright, scarlet-red beam.  Most light sources produce contributions over many wavelengths.  However, humans cannot detect all light, just contributions that fall in the “visible wavelengths”.  Short wavelengths produce a blue sensation, long wavelengths produce a red one.  Spectrophotometer: device used to measure visible light, by reflecting light from a diffraction grating (a ruled surface) that spreads out the different wavelengths.

Color Science  Figure 4.1 shows the phenomenon that white light contains all the colors of a rainbow.  Visible light is an electromagnetic wave in the range 400 nm to 700 nm (where nm stands for nanometer, 10 − 9 meters).

Color Science  Fig. 4.2 shows the relative power in each wavelength interval for typical outdoor light on a sunny day. This type of curve is called a Spectral Power Distribution (SPD) or a spectrum.  The symbol for wavelength is λ. This curve is called E( λ ).

Human Vision  The eye works like a camera, with the lens focusing an image onto the retina (upside-down and left-right reversed).  The retina consists of an array of rods and three kinds of cones.  The rods come into play when light levels are low and produce a image in shades of gray (“all cats are gray at night!”).  For higher light levels, the cones each produce a signal. Because of their differing pigments, the three kinds of cones are most sensitive to red (R), green (G), and blue (B) light.  It seems likely that the brain makes use of differences R-G, G-B, and B-R, as well as combining all of R, G, and B into a high-light- level achromatic channel.

Spectral Sensitivity of the Eye  The eye is most sensitive to light in the middle of the visible spectrum.  The sensitivity of our receptors is also a function of wavelength (Fig. 4.3below).  The Blue receptor sensitivity is not shown to scale because it is much smaller than the curves for Red or Green — Blue is a late addition, in evolution.  Statistically, Blue is the favorite color of humans, regardless of nationality — perhaps for this reason: Blue is a latecomer and thus is a bit surprising!  Fig. 4.3 shows the overall sensitivity as a dashed line — this important curve is called the luminous-efficiency function.  It is usually denoted V ( λ ) and is formed as the sum of the response curves for Red, Green, and Blue.

Spectral Sensitivity of the Eye  The rod sensitivity curve looks like the luminous- efficiency function V ( λ ) but is shifted to the red end of the spectrum.  The achromatic channel produced by the cones is approximately proportional to 2R+G+B/20.

Spectral Sensitivity of the Eye  The response in each color channel in the eye is proportional to the number of neurons firing.  A laser light at wavelength λ would result in a certain number of neurons firing. An SPD is a combination of single-frequency lights (like “lasers”), so we add up the cone responses for all wavelengths, weighted by the eye’s relative response at that wavelength.

Image Formation  Surfaces reflect different amounts of light at different wavelengths, and dark surfaces reflect less energy than light surfaces.  Fig. 4.4 shows the surface spectral reflectance from (1) orange sneakers and (2) faded blue jeans. The reflectance function is denoted S( λ ).

Image Formation

 Image formation is thus: 1. Light from the illuminant with SPD E( λ ) impinges on a surface, with surface spectral reflectance function S( λ ), is reflected, and then is filtered by the eye’s cone functions q ( λ ). 2. Reflection is shown in Fig. 4.5 below 3. The function C( λ ) is called the color signal and consists of the product of E( λ ), the illuminant, times S( λ ), the reflectance: C( λ ) = E( λ ) S( λ ).

Camera Systems  Camera systems are made in a similar fashion; a studio quality camera has three signals produced at each pixel location (corresponding to a retinal position).  Analog signals are converted to digital, truncated to integers, and stored. If the precision used is 8-bit, then the maximum value for any of R,G,B is 255, and the minimum is 0.  However, the light entering the eye of the computer user is that which is emitted by the screen—the screen is essentially a self-luminous source. Therefore we need to know the light E( λ ) entering the eye.