1. Aum Amriteswaryai Namah:
Introduction to
DIGITAL IMAGE PROCESSING
Referance:-Digital Image Processing by Rafeal C Gonzalez &Richard E Woods
Seminar by
Remya,
P2VLD08015,S3 MTech
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2. What is DIP?
Digital: operating by the use of discrete signals to represent data in the form of numbers.
Image: an artifact, usually two dimensional, that has a similar appearance to some subject—usually a physical object or a person.
Processing: to perform operations on data according to programmed instructions.
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3. Definitions:
“Digital Image processing is the use of computer algorithms to perform image processing on digital images.”
“Digital Image processing is electronic data processing on a 2D array of numbers.” The array is a numeric representation of an image.
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4. 1. Improvement of pictorial information for human interpretation
Interest in digital image processing stems from two principal applications areas:
1. Improvement of pictorial information for human interpretation
2. Processing of image data for storage, transmission, and representation for autonomous machine perception
Things which we see are not by themselves what we see …..
It remains completely unknown to u
what the objects may be by themselves and
apart from the receptivity of our senses.
We know nothing but our manner of perceiving them.
----Immanual Kant
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5. The retinal image is reflected in the region of fovea.
There’s more to it than meets the eye.
–19th century proverb
To focus on distant objects, the controlling muscles cause the lens to be relatively flattened.
To focus on near objects, these muscles allow the lens to become thicker.
while focusing distant objects, the lens exhibit lowest refractive power and vice versa.
The retinal image is reflected in the region of fovea.
Perception takes place by the relative excitation of light receptors, which transform radiant energy into electrical impulses that are utlimately decoded by the brain.
Refractive index n = c(velocity of light)/velocity
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6. Brightness Adaptation and Discrimination
Digital images are displayed as a discrete set of intensities.
The intensity perceived by the human visual system is termed as subjective brightness.
Subjective brightness is a logarithmic function of the light intensity incident on the eye.
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7. The visual system cannot operate over such a dynamic range simultaneously.
It accomplishes this large variation by changes in its overall sensitivity, a phenomenon known as brightness adaptation.
The ability of eye to discriminate between changes in light intensity at any specific adaptation is also important.
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8. The quantity ∆IC/I, where ∆IC is the increment of illumination discriminable 50% of the time with background illumination is called the Weber Ratio.
Large Weber ratio means Poor discrimination & small Weber ratio means better discrimination.
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9. Perceived brightness is not a simple function of intensity
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12. A simple image formation Model
An image can be represented by two dimensional functions of the form f(x,y).
The value or amplitude of f at spatial coordinates (x,y) is a positive scalar quantity whose physical meaning is determined by the source of the image.
When an image is generated from a physical process,its values are proportional to energy radiated by a physical source
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13. Function f is characterised by
0<f(x,y)<∞
Function f is characterised by
The amount of source illumination incident on the scene being viewed.illuminationi(x,y)
The amount of illumination reflected by the objects in the scene.reflectancer(x,y)
Thus f(x,y)=i(x,y)r(x,y)
where 0<i(x,y)<∞ and 0<r(x,y)<1
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14. is the intensity of a monochrome image at any coordinates (x0 , y0)
Gray level(l)
is the intensity of a monochrome image at any coordinates (x0 , y0)
l=f(x0,y0)
Lmin ≤ l ≥ Lmax
Lmin must be positive and Lmax must be finite.
The interval [Lmin,Lmax] is called gray scale.
Usually, the interval is considered as [0,L-1].(B&W)
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15. Image Sampling and Quantization.
An image f(x,y) is a continous one.
Digitizing the coordinate values is called sampling.
Digitizing the amplitude values is called quantization.
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16. Sampling process
partitioning the xy plane into a grid, with the coordinates of the center of each grid being a pair of elements (zi,zj)from Z.
Quantisation
 assigns a gray level value to each distinct pair of coordinates and that is the function f.
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17. Representing Digital Images
The result of sampling and quantisation is a matrix of real numbers.
Each element is called an image element, picture element, pixel or pel
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18. The number of bits required to store a digitized image is
If the gray levels are also integers, Z replaces R and a digital image then becomes a 2D function whose coordinates and amplitude values are integers.
Thus the size of an image will be M X N X L where L is the number of gray levels and it must be equal to an integer power of 2.
The range of values spanned by the gray scale is called the dynamic range of an image.
Thus an image with high dynamic range is said to have high contrast and vice versa.
The number of bits required to store a digitized image is
b = M X N X k
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19. Spatial and Gray level Resolution
Sampling is the principal factor determining the spatial resolution.
Spatial resolution of an image is the smallest discernible detail in an image.
For egs, in a chart with vertical lines of width W and spaces with width W,
A line pair consists of a vertical line with width W and the space between two such lines with width W.
Thus the width of a line pair is 2W .
Hence, there are 1/2W line pairs per unit distance.resolution
Gray level resolution refers to the smallest discernible change in gray level.
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23. Varying N and K together…..,
Isopreferance curves
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24. If the function is undersampled ,aliasing corrupts the entire image.
Shanon sampling theorem
If the function is sampled at a rate equal to or greater than twice its highest frequency ,it is possible to recover completely the original function from its samples.
If the function is undersampled ,aliasing corrupts the entire image.
The corruption is in the form of additional frequency components into the sampled functions and these frequencies are called as aliased frequencies.
The sampling rate in images is the number of samples taken per unit distance.
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26. Zooming and shrinking Digital images.
Zooming can be viewed as oversampling and shrinking can be viewed as undersampling.
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27. Image Enhancement in the spatial domain
Spatial domain refers to the aggregate of pixels composing an image.
Spatial domain methods are the procedures that operate directly on pixels.
g(x,y) = T[f(x,y)]
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28. Consider the simplest form of T when the neighborhood is of size 1 X 1,
ie, g depends on value at only f(x,y) and T becomes a gray level transformation function of the form,
s=T(r)
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29. Basic gray level transformations
Here, T(r) produces a two level (binary) image. A mapping of this form is called a threshold function.
Since enhancement at any point in an image depends only on the gray level at that point, this technique is called point processing.
Basic gray level transformations
Image negatives
Log Transformations
Piecewise linear transformations
Contrast stretching
Gray level slicing
Bit plane slicing
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30. Image Negatives
The negative of an image with gray levels in the range [0,L-1] is obtained by using the negative transformation,
s = L – 1 - r
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31. The general form of the log transformation is s = clog(1+r)
Log Transformations
The general form of the log transformation is
s = clog(1+r)
where c is constant and r≥0
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33. Contrast stretching
Increase the dynamic range of gray levels in the image being processed.
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34. Gray level slicing Highlighting a specific range of gray levels.
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35. Bit level slicing
Instead of high lighting gray level ranges, high lighting the contribution made to total image appearance by specific bits
The higher order bits contain the majority of the visually significant data.
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38. This makes you feel sad rather than…..
See this picture….,
This makes you feel sad rather than…..
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39. One picture is worth more than ten thousand words!!!
……reading that “the boy is sad…..
Because….,
One picture is worth more than ten thousand words!!!
Thus image processing is important!!!!
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40. Namah shivaya
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