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CCU, TaiwanWen-Nung Lie
Chapter 6 : Color Image Processing
6-1CCU, TaiwanWen-Nung Lie
Color FundamentalsSpectrum that covers visible colors : 400 ~ 700 nmThree basic quantities
Radiance : energy that flows from the light source (measured in Watts)Luminance : a measure of energy an observer perceives from a light source (in lumens)Brightness : a subjective descriptor difficult to measure
6-2CCU, TaiwanWen-Nung Lie
About human eyesPrimary colors for standardization
blue : 435.8 nm, green : 546.1 nm, red : 700 nm
Not all visible colors can be produced by mixing these three primaries in various intensity proportionsCones in human eyes are divided into three sensing categories
65% are sensitive to red light, 33% sensitive to green light, 2% sensitive to blue (but most sensitive) The R, G, and B colors perceived by human eyes cover a range of spectrum
6-3CCU, TaiwanWen-Nung Lie
Primary and secondary colors of light and pigments
Secondary colors of lightmagenta (R+B), cyan (G+B), yellow (R+G)R+G+B=white
Primary colors of pigmentsmagenta, cyan, and yellowM+C+Y=black
6-4CCU, TaiwanWen-Nung Lie
ChromaticityHue + saturation = chromaticity
hue : an attribute associated with the dominant wavelength or dominant colors perceived by an observersaturation : relative purity or the amount of white light mixed with a hue (the degree of saturation is inversely proportional to the amount of added white light)
Color = brightness + chromaticityTristimulus values (the amount of R, G, and B needed to form any particular color : X, Y, Z
trichromatic coefficients :
)/( ZYXXx ++= )/( ZYXYy ++= )/( ZYXZz ++=
6-5CCU, TaiwanWen-Nung Lie
Chromaticity diagramShow color composition as a function of x, y, and zSpectrum colors are indicated around the boundary of the tongue-shaped chromaticity diagramPoint of equal energy : equal fractions of three primary colors CIE defined white lightPoints located on the boundary of chromaticity diagram are fully saturated -- the saturation at the center point is zero
6-6CCU, TaiwanWen-Nung Lie
Chromaticity diagram (cont.)A straight line segment joining any two points defines all color variations of the combination of themNo three colors in the diagram can span the whole color space -- not all colors can be obtained with three single and fixed primariesThe color gamut produced by RGB monitors The color printing gamut is irregularly-shaped
6-7CCU, TaiwanWen-Nung Lie
Color models, Color spaceA color model is a specification of a coordinate system within which each color is represented by a single pointHardware-oriented color models
e.g., color monitors and printersRGB, CMY (cyan, magenta, yellow), CMYK (+black)
Application-oriented color modelHSI (hue, saturation, intensity)
6-8CCU, TaiwanWen-Nung Lie
RGB color modelEach color appears in its primary spectral components of R, G, and BBased on a Cartesian coordinate system (cube)
6-9CCU, TaiwanWen-Nung Lie
CMY and CMYK color modelsUseful in color printers and copiersConversion between RGB and CMY
In practice, combining CMY colors produces a muddy-looking black. To produce true black, a forth color, black, is added CMYK color model
=
BGR
YMC
111
6-10CCU, TaiwanWen-Nung Lie
HSI color modelRGB, CMY, and similar others are not practical for human interpretationHue : a color attribute that describes a pure colorSaturation : a measure of the degree to which a pure color is diluted by white lightDerivation of HSI from RGB color cube
All points contained in the plane segment defined by the intensity axis (i.e., from black to white) and one color point on the boundaries of the cube have the same hue
6-11CCU, TaiwanWen-Nung Lie
HSI color model (cont)The HSI space is represented by a vertical intensity axis, the length (saturation) of a vector from the axis to a color point, and the angle (hue) this vector makes with the red axisThe power of HSI color model is to allow independent control over hue, saturation, and intensity
6-12CCU, TaiwanWen-Nung Lie
Conversion between RGB and HSI
From RGB to HSI
From HSI to RGBRG sector (0
6-13CCU, TaiwanWen-Nung Lie
Conversion between RGB and HSI (cont)
GB sector (120
6-14CCU, TaiwanWen-Nung Lie
HSI RGB
RGB
HSI
6-15CCU, TaiwanWen-Nung Lie
YUV color modelYUV color model has been used in PAL TV systems.The luminance Y can be determined from RGB model asThe other two chrominance components, U and V, are defined as color difference as
For Completeness, an expression of YUV in terms of RGB is listed below
=
BGR
VUY
100.0515.0615.0436.0289.0147.0114.0587.0299.0
BGRY 114.0587.0299.0 ++=
)(877.0 )(493.0 YRVYBU ==
6-16CCU, TaiwanWen-Nung Lie
YCbCr color modelIt is noted that U and V may be negative as well. In order to make chrominance components nonnegative, the Y, U and V are shifted to produce the YCbCr model, which is used in the international coding standards JPEG and MPEG
The inverse operation
+
=
12812816
439.0291.0148.0071.0368.0439.0
098.0504.0257.0
BGR
CbCrY
)128(017.2)16(164.1')128(392.0)128(813.0)16(164.1'
)128(596.1)16(164.1'
+==
+=
CbYBCbCrYG
CrYR
Reference: B.G. Haskell, A. Puri, A.N. Netravali, Digital Video: An introduction to MPEG-2, Chapman & Hail, 1997Y.Q. Shi, H. Sun, Image and Video compression for multimedia engineering, CRC press, 1999
6-17CCU, TaiwanWen-Nung Lie
Conversion between YUV and YCbCr
From YUV to YCbCr
+
=
12812816
714.0000007.1000860.0
VUY
CrCbY
6-18CCU, TaiwanWen-Nung Lie
Gray level to color transformation -- pseudocolor
Three independent transformation on the graylevels, i.e., establish a color mapping system for graylevelsSome standardized CMSs exist, e.g., ironball for infrared image displayIf all three transforms are the same --> monchrome
6-19CCU, TaiwanWen-Nung Lie
Effect of different gray to color transformations
6-20CCU, TaiwanWen-Nung Lie
Color composition for multi-spectral images
Often used in display of multi-spectral satellite imagesMap three bands out of multi-spectra into RGB for color display
RGB = (red, green, blue)
RGB = (near IR, green, blue)
6-21CCU, TaiwanWen-Nung Lie
Full-color image processingFull-color and interpretations of its various color-space componentsMethod 1
Process each component image individually and form a composite processed color image from the individually processed components
Method 2Work with color pixels directly
6-22CCU, TaiwanWen-Nung Lie
There is a discontinuity in HSI model where 0 and 360of hue meet
Hue is undefined for 0 saturation
6-23CCU, TaiwanWen-Nung Lie
Color transformationTransform a vector in color space to another vector -- color mapping function
Transformation on a per-color-component basis
Some operations are better suited to specific models
Modify pixel intensity HSI is suitable (but the cost for conversion from RGB or CMY to HSI is costly)
nirrrTs nii ,...,2,1 ,),...,,( 21 ==
nirTs iii ,...,2,1 ,)( ==
6-24CCU, TaiwanWen-Nung Lie
Saturation should be altered to implement complement
Color complements
Color circle
Approximation only
6-25CCU, TaiwanWen-Nung Lie
Color slicing
>
= otherwise
2 ,5.0
nj1
i
anyjj
i
r
Warifs
nir
Rarifsi
jji ,...2,1 ,
otherwise
)( ,5.0n
1j
20
2
=
>= =
(a1, a2, ,an) is the prototype or average color
Highlighting a specific range of colors in an image
6-26CCU, TaiwanWen-Nung Lie
Device-independent color model (CIE L*a*b* model)
Unlike RGB and CMY which are specific for certain devices (monitors and printers)Characteristics of L*a*b* color model
The choice for many color management system (CMS)Being colorimetricPerceptually uniform (color differences are perceived uniformly)Device-independentEncompass the entire visible spectrum and can represent accurately the colors of any display, print, or input deviceAn excellent decoupler of intensity (L*) and color (a* : red minus green, b* : green minus blue), making it useful in both image manipulation and image compression applications
6-27CCU, TaiwanWen-Nung Lie
CIE L*a*b* model
are reference white tristimulas values and X, Y, and Z are tristimulas values of any colorThe degree to which the luminance is separated from the color in L*a*b* is greater than in other color models
+>
=008856.0 116/16787.7008856.0 ,)(
3
qqqqqh
=
=
=
WW
WW
W
ZZh
YYhb
YYh
XXha
YYhL
200
500*
16116
*
*
),,( WWW ZYX
6-28CCU, TaiwanWen-Nung Lie
Color image tonal correction Tonal correction to provide a proper key (tone) of an image (just like to correct the brightness of a graytone image)
Hue of color is not changedFor RGB and CMYK -- map all color components with the same transformation functionFor HSI only the intensity component is modified
6-29CCU, TaiwanWen-Nung Lie
Tonal correction
6-30CCU, TaiwanWen-Nung Lie
Color image histogram equalization
Modify brightness and contrast without influencing the hue and saturation
Operation on intensity component only (e.g., HSI model)
Adjustment of hue or saturation is common when working with the intensity component in HSI space since change in intensity usually affect the relative appearance of colors in an image
6-31CCU, TaiwanWen-Nung Lie
Histogram equalization
6-32CCU, TaiwanWen-Nung Lie
Color balancing correction
To reduce magenta remove both red and blue or add greenThe color ring is useful as a reference tool for identifying color printing problem
6-33CCU, TaiwanWen-Nung Lie
Color image smoothing)1( SIB =
Smoothing on independent R, G, and B planesSmoothing on intensity plane of HSI modelThe above two results are different
])60cos(
cos1[H
HSIR
+=o
)(3 BRIG +=
When I increases with B, R, and G
6-34CCU, TaiwanWen-Nung Lie
Color image sharpeningSharpening on independent R, G, and B planesSharpening on intensity plane of HSI modelThe above two results are different
6-35CCU, TaiwanWen-Nung Lie
Color segmentation -- in HSI space
To extract image regions that have desired range of colors
processing on hue imagesaturation image is used as masking to isolate ROIless frequently used for intensity image
Binary saturation mask
Grayscale histogramming of (f)
6-36CCU, TaiwanWen-Nung Lie
Color segmentation -- in RGB space
Measure color similarity in terms of Euclidean distance
within spherical, elliptical, or bounded box region
Get much more accurate result than in HSI space
result
matrixcovariance: )]()[(or ),( 2
11
CazCazazaz = TD
6-37CCU, TaiwanWen-Nung Lie
Color edge detectionGradient operation defined on color vectors
bgruxB
xG
xR
+
+
= bgrvyB
yG
yR
+
+
=
222
xB
xG
xRgxx
+
+
== uu222
yB
yG
yRg yy
+
+
== vv
yB
xB
yG
xG
yR
xRgxy
+
+
== vu
=
)(2
tan21 1
yyxx
xy
ggg
[ ] 21
2sin22cos)()(21)(
+++= xyyyxxyyxx gggggF
r,g,b : Unit vectors along R, G, and B axes
: direction of maximum change
F() : Rate of change (gradient)
6-38CCU, TaiwanWen-Nung Lie
Computing the gradients on individual images and then adding them to form a composite gradient image will lead to different results from those obtained by gradient operation on color vectorsEdge detail of the vector gradient image is more completeMore computational burden for vector gradient operation
6-39CCU, TaiwanWen-Nung Lie
Vector gradient
Individual gradients difference
6-40CCU, TaiwanWen-Nung Lie
Noise in color imagesHow noise carries over when converting from one color model to another
Fine grain noise tends to be less visually noticeable in a color image than it is in a monochrome imageSignificantly degrade the hue and saturation components of the noisy images, but slightly smooth out the intensity image (since I=(R+G+B)/3)
6-41CCU, TaiwanWen-Nung Lie
Less visually noticeable
HSI model
6-42CCU, TaiwanWen-Nung Lie
When only one RGB channel is affected by noise, conversion to HSI spreads the noise to all HSI component images
Noise on green channel
Chapter 6 : Color Image ProcessingColor FundamentalsAbout human eyesPrimary and secondary colors of light and pigmentsChromaticityChromaticity diagramChromaticity diagram (cont.)Color models, Color spaceRGB color modelCMY and CMYK color modelsHSI color modelHSI color model (cont)Conversion between RGB and HSIConversion between RGB and HSI (cont)HSI RGBYUV color modelYCbCr color modelConversion between YUV and YCbCrGray level to color transformation -- pseudocolorEffect of different gray to color transformationsColor composition for multi-spectral imagesFull-color image processingColor transformationColor complementsColor slicingDevice-independent color model (CIE L*a*b* model)CIE L*a*b* modelColor image tonal correctionColor image histogram equalizationColor balancing correctionColor image smoothingColor image sharpeningColor segmentation -- in HSI spaceColor segmentation -- in RGB spaceColor edge detectionNoise in color images