Multimedia Data Introduction to Image Data

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Multimedia DataIntroduction to Image Data
This lecture provides a short introduction to
image anatomy that will provide useful background
for image processing and image compression which
we will consider shortly.

• Dr Sandra I. Woolley
• http//www.eee.bham.ac.uk/woolleysi
• S.I.Woolley_at_bham.ac.uk
• Electronic, Electrical and Computer Engineering

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Content

• The contents of an image file.
• Simple test images.
• Image histograms and pixel correlations
• The .raw file

Cheetah test image.

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Digital Image Data
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Producing a Digital Image
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Image Pixels

• Image pixels form a natural matrix that we can
  easily label.
• The picture on the right shows the pixels
  labelled as (x,y).
• Starting at the top left at (0,0) x increases in
  the horizontal direction and y increases
  vertically down.
• We could label them differently if we wanted.
  The important thing is that we can unambiguously
  identify them.
• There are TWO easy ways to confuse pixel
  locations.
• Mixing up numbers that start at (0,0) with ones
  start at (1,1).
• Mixing (x,y) notation and (row, column). (row,
  column) is (y,x).

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mouse
320

• Mouse.raw has 320x200 pixels. It is a simple but
  effective test image.
• Mouse is an 8-bit greyscale test image. We will
  study colour later. 8 bits per pixel (bpp) means
  we have 256 values (Black0 white 255).
• The x-axis of the image histogram is intensity
  (colour) from Black0 to white255.

200
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Paintshop Pro Software (Jasc)

• Paintshop Pro (made by Jasc) is a useful tool for
  manipulating images.
• Newer shareware version is time limited.
• The image on the right shows mouse in PaintShop
  Pro after it has been lightened. Notice the
  histogram has moved to the right (remember
  black0 and white255)
• FastStone (www.faststone.org) is a freeware
  alternative. See download sites (such as
  www.snapfiles.com) for downloads.) FastStone
  does not support .raw not save files as .gif to
  open.
• Faststone histograms are in the Edit menu.

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Paintshop Pro Software (Jasc)

• Notice the different histogram for the cheetah
  image.
• The image uses a wider range of intensity values
  than the mouse picture.
• Mouse is a very simple picture. Real world
  images are usually more complex. They tend to
  have histograms more like cheetahs , i.e.,
  flatter, because they contain a wider range of
  colours.

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Differencing Neighbouring Pixels

• The actual difference in value between adjacent
  pixels is often very small.
• The histograms on the right show the pixel values
  for the cheetah image before and after pixel
  differencing.
• The differenced values can be compressed more
  efficiently.

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A Closer Look at Mouse
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Reducing Resolution (a bad way to compress)
Mouse at 80x50 Pixels
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Mouse at 40x25 Pixels
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Mouse With Only 16 Colours (i.e.,4 Bits Per
Pixel)
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Mouse With Just 2 Colours (i.e.,1 Bit Per Pixel)
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Negative Mouse
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Edge Mouse
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Deformation Mouse (punch 72)
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Accessing .raw Image Data
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A Simple ExampleMouse.raw at 10x10 pixels!!

• This is mouse.raw at just 10x10 pixels.
• A .raw file is the simplest type of image file.
  It has no header information and it is not
  compressed.
• The 10x10 image of mouse simply contains only 100
  continuous 8-bit bytes.
• If we try to open a .raw file in PaintShop we
  need to specify the dimensions.

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A Simple ExampleMouse.raw at 10x10 Pixels!!

• If we try to open a .raw file in a simple text
  editor we will see something like this.
• The viewer will interpret the image pixel values
  as ascii alphanumeric or control characters.
• If we want to read (or manipulate) the image
  pixel values we can write a simple program to
  open the file for us.

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A Simple ExampleMouse.raw at 10x10 Pixels!!

• This is an example of output from a simple
  program that prints out the 100 pixel values in
  10 rows of 10.
• Notice that the darkest regions at the bottom of
  of the image are represented by very low values
  as you would expect.
• Similarly the lighter regions of mouse have high
  values (200 and above).

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• This concludes our introduction to image
  processing.
• Next we will look at how to perform simple image
  processing and how we can use compression to
  represent the image without losing too much
  quality.
• You can find course information, including slides
  and supporting resources, on-line on the course
  web page at

Thank You
http//www.eee.bham.ac.uk/woolleysi/teaching/multi
media.htm