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Introduction to Image Processing

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Title: Introduction to Image Processing


1
Introduction to Image Processing
2
What is Image Processing?
  • Manipulation of digital images by computer.
  • Image processing focuses on two major tasks
  • Improvement of pictorial information for human
    interpretation and high level processing.
  • Processing of image data for storage and
    transmission.

3
Related Areas
  • Image Processing
  • Computer Vision
  • Computer Graphics

4
Image Processing
5
Image Processing
  • Image Enhancement

6
Image Processing (contd)
  • Image Restoration

7
Image Processing (contd)
  • Image Compression

8
Computer Graphics
9
Computer Graphics
Projection, shading, lighting models
Output
Image
Synthetic Camera
10
Computer Vision
11
Computer Vision
Cameras
Images
12
Applications Image Enhancement
  • One of the most common uses of IP techniques
    improve quality, remove noise etc

13
Applications Space
  • Launched in 1990 the Hubble telescope can take
    images of very distant objects
  • An incorrect mirror made many of Hubbles
    images useless
  • Image processing techniques were used to fix
    this!

14
Applications Medicine
  • Take slice from MRI scan of a dogs heart, and
    find boundaries between different types of tissue
  • Image with gray levels representing tissue
    density
  • Use a suitable filter to highlight edges

Original MRI image of a dogs heart
Edge detection image
15
Applications GIS
  • Geographic Information Systems
  • Digital image processing techniques are used
    extensively to manipulate satellite imagery.

meteorology
terrain classification
16
Applications Industrial Inspection
  • Human operators are expensive, slow and
    unreliable
  • Make machines do thejob instead!
  • Industrial vision systems are used in all
    kinds of industries

17
Applications Law Enforcement
  • Image processing techniques are used extensively
    by law enforcers

Number plate recognition for speed cameras or
automated toll systems
Fingerprint recognition
18
Examples HCI
  • Make Human Computer Interaction (HCI) more
    natural
  • Face recognition
  • Gesture recognition

19
Key Stages in Digital Image Processing
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
20
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
21
Image Enhancement
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
22
Image Restoration
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
23
Morphological Processing
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
24
Segmentation
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
25
Representation Description
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
26
Object Recognition
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Representation Description
Object Recognition
Problem Domain
Colour Image Processing
Image Compression
27
Image Compression
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Object Recognition
Representation Description
Problem Domain
Colour Image Processing
Image Compression
28
Color Image Processing
Image Restoration
Morphological Processing
Segmentation
Image Enhancement
Image Acquisition
Object Recognition
Representation Description
Problem Domain
Color Image Processing
Image Compression
29
How are images represented in the computer?
30
Color images
31
A Simple model of image formation
32
What is (visible) light?
  • The visible portion of the electromagnetic (EM)
    spectrum.
  • Approximately between 400 and 700 nanometers.

33
Examples Gama-Ray Imaging

Gamma-ray imaging nuclear medicine and
astronomical observations
34
Examples X-Ray Imaging

X-rays medical diagnostics, industry, and
astronomy, etc.
35
Examples Ultraviolet Imaging

Ultraviolet industrial inspection, microscopy,
lasers, biological imaging, and astronomical
observations
36
Examples Infrared Imaging
Infrared bands light microscopy, astronomy,
remote sensing, industry, and law enforcement.
37
Sonic images
  • Produced by the reflection of sound waves off an
    object.
  • High sound frequencies are used to improve
    resolution.

38
Range images
  • Can be produced by using laser range-finders.
  • An array of distances to the objects in the
    scene.

39
Image formation
  • There are two parts to the image formation
    process
  • The geometry of image formation, which determines
    where in the image plane the projection of a
    point in the scene will be located.
  • The physics of light, which determines the
    brightness of a point in the image plane as a
    function of illumination and surface properties.

40
Pinhole camera
  • This is the simplest device to form an image of a
    3D scene on a 2D surface.
  • Straight rays of light pass through a pinhole
    and form an inverted image of the object on the
    image plane.

41
Camera optics
  • In practice, the aperture must be larger to admit
    more light.
  • Lenses are placed in the aperture to focus the
    bundle of rays from each scene point onto the
    corresponding point in the image plane

42
Physics of Light
  • f(x,y)i(x,y)r(x,y)
  • where
  • i(x,y) the amount of illumination
  • incident to the scene
  • 2) r(x,y) the reflectance from the object

43
CCD (Charged-Coupled Device) cameras
  • Tiny solid state cells convert light energy into
    electrical charge.
  • The image plane acts as a digital memory that can
    be read row by row by a computer.

44
Frame grabber
  • Usually, a CCD camera plugs into a computer board
    (frame grabber).
  • The frame grabber digitizes the signal and stores
    it in its memory (frame buffer).

45
Image digitization
  • Sampling means measuring the value of an image at
    a finite number of points.
  • Quantization is the representation of the
    measured value at the sampled point by an integer.

46
Image digitization (contd)
255
0
47
Image digitization (contd)
2D example
48
Effect of Image Sampling
  • original image
    sampled by a factor of 2
  • sampled by a factor of 4
    sampled by a factor of 8

49
Effect of Image Quantization
  • 256 gray levels (8bits/pixel)
    32 gray levels (5 bits/pixel) 16 gray levels
    (4 bits/pixel)
  • 8 gray levels (3 bits/pixel)
    4 gray levels (2 bits/pixel) 2 gray
    levels (1 bit/pixel)

50
Representing Digital Images
The result of sampling and quantization is a
matrix of integer numbers. Here we have an
image f(x,y) that was sampled to produce M rows
and N columns.
51
Representing Digital Images (contd)
  • There is no requirements about M and N
  • Usually L 2k
  • Dynamic Range 0, L-1

The number of bits b required to store an
image b M x N x k where k is the number
of bits/pixel
52
Image file formats
  • Many image formats adhere to the following simple
    model
  • Header
  • Data (line by line, no breaks between lines).

53
Image file formats (cont.)
  • Header contains at least
  • A signature or magic number (i.e., a short
    sequence of bytes for identifying the file
    format).
  • The width and height of the image.

54
Common image file formats
  • PGM (Portable Gray Map)
  • PNG (Portable Network Graphics)
  • GIF (Graphic Interchange Format)
  • JPEG (Joint Photographic Experts Group)
  • TIFF (Tagged Image File Format)
  • FITS (Flexible Image Transport System)
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