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Fundamentals

Parts of these slides base on thetextbook

Digital Image Processingby Gonzales/Woods

Chapters 1 / 2

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These slides show

basic concepts about digital images

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In the beginning

well have a look at the human eye

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Some topics we have to deal with:

Sharpness

Brightness Processing of perceived visual

information

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Sharpness

The eye is able to deal with

sharpness in different distances

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Brightness

The eye is able to adapt to different

ranges of brightness

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What is an image ?

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The retinal model is mathematically hard to

handle (e.g. neighborhood ?)

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Easier: 2D array of cells, modelling the

cones/rods

Each cell contains a numerical value (e.g.between 0-255)

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The positionof each cell defines the position of

the receptor

The numerical valueof the cell represents theillumination received by the receptor

5 7 1 0 12 4

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With this model, we can create GRAYVALUE

images

Value = 0: BLACK (no illumination / energy)

Value = 255: White (max. illumination / energy)

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A 2D grayvalue - image is a 2D -> 1Dfunction,

v = f(x,y)

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As we have a function, we can applyoperators to this function, e.g.

H(f(x,y)) = f(x,y) / 2

Operator Image (= function !)

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H(f(x,y)) = f(x,y) / 2

6 8 2 0

12 200 20 10

3 4 1 0

6 100 10 5

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Remember: the value of the cells is theillumination (or brightness)

6 8 2 0

12 200 20 10

3 4 1 0

6 100 10 5

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As we have a function, we can applyoperators to this function

but why should we ?

some motivation for (digital) imageprocessing

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Transmission of images

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Image Enhancement

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Image Analysis / Recognition

F d l

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The mandatory steps:

Image Acquisition andRepresentation

F d t l

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Typical sensor for images:

CCD Array (Charge Couple Devices)

Use in digital cameras Typical resolution 1024 x 768

(webcam)

F d t l

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CCD

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Representation

Black/White and Color

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Color Representation: Red / Green / Blue

Model for

Color-tube

Note: RGB is not theONLY color-model, in factits use is quiet restricted.

More about that later.

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Color images can be represented by3D Arrays (e.g. 320 x 240 x 3)

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But for the timebeing well handle

2D grayvalueimages

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Digital vs. Analogue Images

Analogue:Function v = f(x,y): v,x,y are REAL

Digital:Function v = f(x,y): v,x,y are INTEGER

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Stepping down from REALity to INTEGER

coordinates x,y: Sampling

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Stepping down from REALity to INTEGER

grayvalues v : Quantization

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Sampling

andQuantization