Image Processing

Ch2: Digital image Fundamentals

Prepared by: Hanan Hardan

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Image Acquisition:

The image is captured by a sensor (eg. Camera), and digitized if the output of the camera or sensor is not already in digital form, using analogue-to-digital convertor

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Image sampling and quantization

In order to process the image, it must be saved on computer.

The image output of most sensors (eg: Camera) is continuous voltage waveform.

But computer deals with digital images not with continuous images, thus: continuous images should be converted into digital form.

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Image sampling and quantization To convert continuous image (in real life) to digital image (in computer) we use Two processes: 1.sampling 2.quantization. Remember that: the image is a function f(x,y), x and y: are coordinates F: intensity value (Amplitude) Sampling: digitizing the coordinate values Quantization: digitizing the amplitude values Thus, when x, y and f are all finite, discrete quantities, we call the image a digital image.

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How does the computer digitize the continuous image?

Ex:

scan a line such as AB from the continuous image, and represent

the gray intensities.

How does the computer digitize the continuous image?

Ex:

scan a line such as AB from the continuous image, and represent

the gray intensities.

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How does the computer digitize the continuous image?

Sampling: digitizing coordinates

Quantization: digitizing intensities

sample is a small white square, located by a vertical tick mark as a point x,y

Quantization: converting each sample gray-level value into discrete digital quantity.

Gray-level scale that divides gray-level into 8 discrete levels

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How does the computer digitize the continuous image? Now:

the digital scanned line AB representation on computer:

The continuous image VS the result of digital image after sampling and quantization

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Digital Image Representation

The result of sampling and quantization is a matrix of real numbers

Assume that an image f(x,y) is sampled so that the resulting image has M rows and N columns. We say that the image is of size M x N. The values of the coordinates (x,y) are discrete quantities. For clarity, we use integer values for these discrete coordinates.

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Digital Image Representation

Images as Matrices

Each element of this array is called an image element, picture element, pixel or pel.

A digital image can be represented naturally as a MATLAB matrix:

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Pixels!

Every pixel has # of bits (k) so, the gray intensities ( L ) that the pixel can hold, is calculated

according to a number of pixels it has (k).

L= 2k Q: Suppose a pixel has 1 bit, how many gray levels can it represent? Answer: 2 intensity levels only, black and white. Bit (0,1) 0:black , 1: white Q:Suppose a pixel has 2 bit, how many gray levels can it represent? Answer: 4 gray intensity levels 2Bit (00, 01, 10 ,11). Now .. if we want to represent 256 intensities of grayscale, how many bits

do we need? Answer: 8 bits which represents: 28=256

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Number of storage of bits:

N * M: the no. of pixels in all the image.

K: no. of bits in each pixel

L: grayscale levels the pixel can represent

L= 2K

all bits in image= N*N*k

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Number of storage of bits:

EX: Here: N=32, K=3, L = 23 =8

# of pixels=N*N = 1024 . (because in this example: M=N)

# of bits = N*N*K = 1024*3= 3072

N=M in this table, which means no. of horizontal pixels= no. of vertical pixels. And thus:

# of pixels in the image= N*N Hanan Hardan 12

Spatial and gray-level resolution

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Spatial and gray-level resolution

Resolution: How Much Is Enough?

This all depends on what is in the image and what you would like to do with it

Key questions include

Can you see what you need to see within the image?

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Resolution: How Much Is Enough? (cont…)

The picture on the right is fine for counting the number of cars, but not for reading the number plate

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Spatial resolution:

Sampling is the principal factor determining the spatial resolution of an image

Basically, spatial resolution is the smallest discernible detail in an image.

Spatial Resolution

( .هي وحدة قياس لاصغر جزء في الصورة يمكن تمييزة بالعين )

, فهو فقط يحد ابعاد الصورة , عدد البكسلات في الصورة لا يحدد وضوحها

فكلما , هو المسؤول عن تحديد الوضوح Spatial resolutionاما

اكثر كان لها قدرة كانت البكسلات متقاربة وتحمل قيم لونيه صحيحة

.اعلى على توضيح معالم الصورة بشكل اوضحHanan Hardan 16

How to choose the spatial resolution

= Sampling locations

Ori

gin

al i

mag

e

Sam

ple

d i

mag

e

Under sampling, we lost some image details!

Spatial resolution

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How to choose the spatial resolution : O

rigin

al i

mag

e

Spatial resolution

(sampling rate)

Sampled image

No detail is lost!

1m

m

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Effect of Spatial Resolution Example:

256x256 pixels

64x64 pixels

128x128 pixels

32x32 pixels

insufficient spatial resolution appearance of checkerboard pattern in the image

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Example: Spatial resolution

الصورة في اليسار تحمل عدد بكسلات اكبر من الصورة في الجهه اليمين

لماذا؟ ومع ذالك الصورة في اليسار تبدوا غير واضحة,

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gray-level resolution

Quantization is the principal factor determining the gray level resolution of an image

Gray-level resolution refers to the smallest discernible change in gray level.

يمكن تمييزها ( كثافة اللون الرمادي)وهي تعني اصغر تغيير في الكثافة

ورؤيتها

Color depth/ levels is given by

kL 2Hanan Hardan 21

Effect of Quantization Levels Example:

256 levels 128 levels

32 levels 64 levels Hanan Hardan 22

Effect of Quantization Levels (cont.)

16 levels 8 levels

2 levels 4 levels

In this image,

it is easy to see

false contour.

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Digital Image Types:

Binary image (B&W)

Grayscale image

Color image (RGB)

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Common image formats include:

1 sample per point (B&W or Grayscale)

3 samples per point (Red, Green, and Blue)

For most of this course we will focus on grey-scale images

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Binary Images

are images that have been Binary images quantized to two values, usually denoted 0 and 1, but often with pixel values 0 and 255, representing black and white.

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Image Types : Binary Image

Binary image or black and white image

Each pixel contains one bit :

1 represent white

0 represents black

1111

1111

0000

0000

Binary data

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Grayscale Images

A grayscale (or graylevel) image is simply one in which the only colors are shades of gray (0 – 255)

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Digital Image Types : Intensity Image

Intensity (monochrome or gray scale) image

each pixel corresponds to light intensity

normally represented in gray scale (gray

level).

39871532

22132515

372669

28161010

Gray scale values

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Color Images

Color image: A color image contains pixels each of which holds three intensity values corresponding to the red, green, and blue or( RGB)

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39871532

22132515

372669

28161010

39656554

42475421

67965432

43567065

99876532

92438585

67969060

78567099

Digital Image Types : RGB Image

Color image or RGB image:

each pixel contains a vector

representing red, green and

blue components.

RGB components

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