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N.Gowthaman-P15274353
S.Kiruthika-P15274354
II M.Sc.,(Computer Science)
SUBMITTED TO
B.SOWBARNIKA M.Sc.,M.Phil.,
Assistant professor,
Department of computer science.
 Introduction
 Color Fundamental
 Color Models
 Pseudo color processing
 Basic of full color image processing
 Color Transformation
 Conclusion
 The characteristics of color image are distinguished by its properties
brightness, hue and saturation.
 simplifies object extraction and identification.
 Motivation to use color
 Brightness
Hue
Motivation to use color:
 Powerful descriptor that often simplifies object identification and extraction
from a scene
 Humans can discern thousands of colour shades and intensities, compared to
about only two dozen shades of gray
Hue:
Attribute associated with the dominant wavelength in a mixture of light
waves
Hue is somewhat synonymous to what we usually refer to as "colors". Red,
green, blue, yellow, and orange are a few examples of different hues.
Mean wavelength of the spectrum
Brightness:
Intensity
Perceived luminance
Depends on surrounding luminance
Color Fundamental:
In 1666 Sir Isaac Newton discovered that when a beam of sunlight passes
through a glass prism, the emerging beam is split into a spectrum of colors
 A chromatic light source, there are 3 attributes to describe the quality:
 Primary colors can be added to produce the secondary colors of light:
 Cyan (green plus blue)
 Yellow (red plus green)
 Magenta (red plus blue)
 The three basic quantitles useds to describe the quantity of a chromatic light
source are:
 Radiance
 Luminance
Brightness
Radiance:
 The total amount of energy that flows from the light source (measured in watts)
Luminance:
 The amount of energy an observer perceives from the light source (measured in
lumens)
 we can have high radiance, but low luminance
Brightness:
 A subjective (practically unmeasurable) notion that embodies the intensity of light
 Color, by defining a 3D coordinate system, and a subspace that
contains all constructible colors within a particular model.
A color model is an abstract mathematical model describing the
way colors can be represented as tuples of numbers, typically as three or
four values or color components.
 Each color model is oriented towards either specific hardware
(RGB,CMY,YIQ), or image processing applications (HSI).
Any color that can be specified using a model will correspond to a single
point within the subspace it defines
TYPES OF COLOR MODELS:
 RGB Model
 CMY Model
 HSI Model
 YIQ Model
RGB Model:
 Color monitor, color video cameras
 In the RGB model, an image consists of three independent image planes,
one in each of the primary colors: red, green and blue.
 Specifying a particular colour is by specifying the amount of each of the primary
components present.
 The geometry of the RGB colour model for specifying colors using a Cartesian
coordinate system. The greyscale spectrum,
.
 The RGB color cube. The grayscale spectrum lies on the line joining the
black and white vertices.
CMY Model:
 The CMY (cyan-magenta-yellow) model is a subtractive model appropriate
to absorption of colors, for example due to pigments in paints
 Whereas the RGB model asks what is added to black to get a particular color,
the CMY model asks what is subtracted from white.
 In this case, the primaries are cyan, magenta and yellow, with red, green and
blue as secondary colors
 The relationship between the RGB and CMY
HSI Model:
 As mentioned above, colour may be specified by the three quantities hue,
saturation and intensity.
 This is the HSI model, and the entire space of colors that may be specified in
this way is shown
 Conversion between the RGB model and the HSI model is quite
complicated. The intensity is given by
I =R+G+B
 where the quantities R, G and B are the amounts of the red, green and blue
components, normalised to the range [0,1]. The intensity is therefore just the
average of the red, green and blue components.
 The saturation is given by:S = 1 –min
YIQ Model:
 The YIQ (luminance-inphase-quadrature)model is a recoding of RGB
for colour television, and is a very important model for colour image
processing. The importance of luminance was discussed in
 The conversion from RGB to YIQ is given by:
 The luminance (Y) component contains all the information required
for black and white television, and captures our perception of the
relative brightness particular colors.
Pseudo color image processing consists of assigning colors to grey
values based on a specific criterion
The principle use of pseudo color image processing is for human
visualization
Intensity slicing and color coding is one of the simplest kinds of
pseudo color image processing
 Grey level color assignments can then be made according to the
relation
where ck is the color associated with the kth intensity level Vk
defined by the partitioning planes at l = k – 1 and l = k
 Used in the case where there are many monochrome images such as
multispectral satellite images
 Full‐color image processing approaches fall into two major categories
 In the first category, we process each component image individually and
then form a composite processed color image from the individually
processed components
 In the second category, we work with color pixels directly
Color transformations:
 Color transformations can be of the form
 where ri and si are the color components of the input and output images, n
is the dimension of the color space. Ti are referred to as full‐color
transformation or mapping functions
Implementation Tips :
 Linear interpolation by using control points is implemented in
“interp1q”
 Cubic spline interpolation by using control points is Color
implemented in “spline”
 Digital color processing includes processing of colored images and
different color spaces that are used. For example RGB color model,
YCbCr,
 HSV. It also involves studying transmission , storage , and encoding of
these color images.
 The RGB primary commonly used for color display mixes the luminance
and chrominance attributes of a light.
THANKS TO
P. MEERABAI M.C.A.,M.Phil.,
HEAD OF THE DEPARTMENT,
COMPUTER SCIENCE.
Color Image Processing Techniques

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Color Image Processing Techniques

  • 1.
  • 3. SUBMITTED TO B.SOWBARNIKA M.Sc.,M.Phil., Assistant professor, Department of computer science.
  • 4.  Introduction  Color Fundamental  Color Models  Pseudo color processing  Basic of full color image processing  Color Transformation  Conclusion
  • 5.  The characteristics of color image are distinguished by its properties brightness, hue and saturation.  simplifies object extraction and identification.  Motivation to use color  Brightness Hue Motivation to use color:  Powerful descriptor that often simplifies object identification and extraction from a scene  Humans can discern thousands of colour shades and intensities, compared to about only two dozen shades of gray
  • 6. Hue: Attribute associated with the dominant wavelength in a mixture of light waves Hue is somewhat synonymous to what we usually refer to as "colors". Red, green, blue, yellow, and orange are a few examples of different hues. Mean wavelength of the spectrum Brightness: Intensity Perceived luminance Depends on surrounding luminance Color Fundamental: In 1666 Sir Isaac Newton discovered that when a beam of sunlight passes through a glass prism, the emerging beam is split into a spectrum of colors
  • 7.  A chromatic light source, there are 3 attributes to describe the quality:  Primary colors can be added to produce the secondary colors of light:  Cyan (green plus blue)  Yellow (red plus green)  Magenta (red plus blue)
  • 8.  The three basic quantitles useds to describe the quantity of a chromatic light source are:  Radiance  Luminance Brightness Radiance:  The total amount of energy that flows from the light source (measured in watts)
  • 9. Luminance:  The amount of energy an observer perceives from the light source (measured in lumens)  we can have high radiance, but low luminance Brightness:  A subjective (practically unmeasurable) notion that embodies the intensity of light
  • 10.  Color, by defining a 3D coordinate system, and a subspace that contains all constructible colors within a particular model. A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components.  Each color model is oriented towards either specific hardware (RGB,CMY,YIQ), or image processing applications (HSI). Any color that can be specified using a model will correspond to a single point within the subspace it defines
  • 11. TYPES OF COLOR MODELS:  RGB Model  CMY Model  HSI Model  YIQ Model RGB Model:  Color monitor, color video cameras  In the RGB model, an image consists of three independent image planes, one in each of the primary colors: red, green and blue.  Specifying a particular colour is by specifying the amount of each of the primary components present.  The geometry of the RGB colour model for specifying colors using a Cartesian coordinate system. The greyscale spectrum, .
  • 12.  The RGB color cube. The grayscale spectrum lies on the line joining the black and white vertices. CMY Model:  The CMY (cyan-magenta-yellow) model is a subtractive model appropriate to absorption of colors, for example due to pigments in paints  Whereas the RGB model asks what is added to black to get a particular color, the CMY model asks what is subtracted from white.  In this case, the primaries are cyan, magenta and yellow, with red, green and blue as secondary colors
  • 13.  The relationship between the RGB and CMY HSI Model:  As mentioned above, colour may be specified by the three quantities hue, saturation and intensity.  This is the HSI model, and the entire space of colors that may be specified in this way is shown
  • 14.  Conversion between the RGB model and the HSI model is quite complicated. The intensity is given by I =R+G+B  where the quantities R, G and B are the amounts of the red, green and blue components, normalised to the range [0,1]. The intensity is therefore just the average of the red, green and blue components.  The saturation is given by:S = 1 –min
  • 15. YIQ Model:  The YIQ (luminance-inphase-quadrature)model is a recoding of RGB for colour television, and is a very important model for colour image processing. The importance of luminance was discussed in  The conversion from RGB to YIQ is given by:  The luminance (Y) component contains all the information required for black and white television, and captures our perception of the relative brightness particular colors.
  • 16. Pseudo color image processing consists of assigning colors to grey values based on a specific criterion The principle use of pseudo color image processing is for human visualization Intensity slicing and color coding is one of the simplest kinds of pseudo color image processing  Grey level color assignments can then be made according to the relation where ck is the color associated with the kth intensity level Vk defined by the partitioning planes at l = k – 1 and l = k
  • 17.  Used in the case where there are many monochrome images such as multispectral satellite images
  • 18.  Full‐color image processing approaches fall into two major categories  In the first category, we process each component image individually and then form a composite processed color image from the individually processed components  In the second category, we work with color pixels directly Color transformations:  Color transformations can be of the form  where ri and si are the color components of the input and output images, n is the dimension of the color space. Ti are referred to as full‐color transformation or mapping functions
  • 19. Implementation Tips :  Linear interpolation by using control points is implemented in “interp1q”  Cubic spline interpolation by using control points is Color implemented in “spline”
  • 20.  Digital color processing includes processing of colored images and different color spaces that are used. For example RGB color model, YCbCr,  HSV. It also involves studying transmission , storage , and encoding of these color images.  The RGB primary commonly used for color display mixes the luminance and chrominance attributes of a light.
  • 21. THANKS TO P. MEERABAI M.C.A.,M.Phil., HEAD OF THE DEPARTMENT, COMPUTER SCIENCE.