Week 3 Sp05

1
IT-101
Introduction to Information Technology

• Week 3Sp05

2
Overview

• Calculating Bits vs. Bytes
• Ch 5 From the Real World to Images Video
• Introduction to Visual Representation and Display
• Digitizing Gray Scale Images
• Digitizing Color Images
• Digital Video
• Chapter 8 Image Compression
• Chapter 9 Digital Video

3
Bits vs. Bytes
1 Byte 8 Bits
Transmission Rates Measured in Bits Per Second

• Bits are often used in terms of a data rate, or
  speed of information flow
• 56 Kilobit per second modem (56 Kbps)
• A T-1 is 1.544 Megabits per second (1.544 Mbps or
  1544 Kbps)
• Bytes are often used in terms of storage or
  capacity--computer memories are organized in
  terms of 8 bits
• 256 Megabyte (MB) RAM
• 40 Gigabyte (GB) Hard disk

Computer Storage and Memory Measured in Bytes
4
Note! The Multipliers for Storage and
Transmission are Slightly Different.
Kilo or Mega have slightly different values
when used with bits per second or with bytes.

• When Referring to Bytes (as in computer memory
  i.e. storage)
• Kilobyte (KB) 210 1,024 bytes
• Megabyte (MB) 220 1,048,576 bytes
• Gigabyte (GB) 230 1,073,741,824 bytes
• When Referring to Bits Per Second (as in
  transmission rates)
• Kilobit per second (Kbps) 1000 bps (thousand)
• Megabit per second (Mbps) 1,000,000 bps
  (million)
• Gigabit per second (Gbps) 1,000,000,000 bps
  (billion)

5
More Multipliers for Measuring Bytes

• Kilobyte (K) 210 1,024 bytes
• Megabyte (M) 220 1,048,576 bytes
• Gigabyte (G) 230 1,073,741,824 bytes
• Terabytes (T) 240 1,099,511,627,776 bytes
• Petabytes (P) 250 1,125,899,906,842,624 bytes
• Exabytes (E) 260 1,152,921,504,606,846,976
  bytes
• Zettabytes (Z) 270 1,180,591,620,717,411,303,424
  bytes
• Yottabytes (Y) 280 1,208,925,819,614,629,174,706
  ,176 bytes

6
Bits vs. Bytes Some Examples

• Calculate how many bits per second are
  transmitted over a bluetooth connection with a
  data transfer rate of 721Kbps
• 1Kbps 1000 bits per second
• So, 721Kbps 721 x 1000 721,000 bits per
  second
• Calculate the number of bits that can be stored
  on an Apple iPod with a 40GB hard drive
• 1 GB 230 bytes 1,073,741,824 bytes
• 40 GB 40 x 1,073,741,824 bytes 42,949,672,960
  bytes
• 1 byte 8 bits . So,
• 42,949,672,960 Bytes 8 x 42,949,672,960
  343,597,383,680 bits

7
More Exercises

• Transmission
• Calculate how many bits per second are
  transmitted with a 56Kbps modem
• Calculate how many bits per second are
  transmitted over a fiber optic cable that can
  carry 1.25Gbps of data
• Storage
• Calculate the number of bits that can be stored
  on a 700MB CD
• Calculate the number of bits in a 4.6KB word
  document stored on your hard disk
• Calculate the number of Bytes in a 2MB image you
  received through email

8
Introduction to Visual Representation and Display

• In the previous chapters, you learned how to
  represent information that was in the form of
  numbers and text
• In this chapter, you will learn how to represent
  still and time varying images with binary digits
• Images play a fundamental role in the
  representation, storage and transmission of
  information.

9
Image Issues

• The world we live in is analog, or continuously
  varying.
• We lose information while digitizing, so we make
  approximations and determine the tradeoffs
  involved.
• While digitizing, we need to consider the
  following facts
• We are producing information for human use
• Take advantage of the fact that human vision has
  limitations
• Produce displays that are good enough for the
  particular application

10
Digital Information for Humans

• Many digital systems take advantage of human
  limitations (visual, aural, etc)
• Most people can detect at most 50 different
  shades of gray
• The human eye can resolve about 60 lines per
  degree of visual arc- a measure of the ability
  of the eye to resolve fine detail
• When we look at a 8.5 x 11 sheet of paper at 1
  foot (landscape) the viewing angles are 49.25
  degrees for the horizontal dimension, and 39
  degrees for the vertical dimension
• We can therefore distinguish
• 49.25 degrees x 60 2955 horizontal lines
• 39 degrees x 60 2340 vertical lines
• These numbers give us a clue about the length of
  the code needed to encode images

11

• To form a black line, you need two rows of pixels
  (one black and one white) to give a visual clue
  of the transition from black to white
• For our paper example
• Number of pixels needed to represent total image
  on a page (2 x 2955) x (2 x 2340) 27,658,800
  pixels per page
• This number of pixels would be sufficient to
  represent any image on the page with no visible
  degradation compared to a perfect analog
  (unpixelized) image at a distance of one foot

12

• lines per degree of visual arc
• Image brought closer to the eye, we can resolve
  more detail

Visual Arc
13
Pixels

• A pixel is the smallest unit of representation
  for visual information
• Each pixel in a digitized image represents one
  intensity (brightness) level (gray scale or
  color)

13 x 13 grid 169 pixels
Gray scale
Color
14
How many pixels should be used?

• The number of pixels used in an image depends on
  the desired spatial resolution.
• High spatial resolution means that the image
  contains a large number of pixels.
• As the number of pixels that form an image
  (spatial resolution) increases when the size of
  the image is held constant, the amount of data
  that needs to be transmitted, stored or processed
  increases as well. However, the image is high in
  quality as a result.
• So, an artist would most probably want a high
  resolution image, and an Internet user would
  settle for low resolution to minimize download
  time.

15
How many pixels should be used?
While keeping the image at a fixed size, if too
few pixels used, image appears coarse
16 x16 (256 pixels)

64 x 64 (4096 pixels)
16
A note about device resolution

• When dealing with printers, we often quote the
  resolution (spatial) in terms of dots per inch
  (dpi), which corresponds to pixels per inch in
  our example

17
Printer Resolution

• DPI
• It is popular to set laser or ink-jet printer
  settings to 600 dpi of resolution
• However, if we hold the paper closer, we would
  need a greater resolution printer for example
  720 dpi, 1200 dpi or greater

18
Camera Resolution

• Megapixel
• When buying a digital camera, we are primarily
  concerned with its spatial resolution
• Digital cameras nowadays come with a range of
  spatial resolutions, from less than 1 megapixels
  to more than 10 megapixels

19
Digitizing Gray Scale Images

• The first step to digitize a black and white
  (gray scale) image composed of an array of gray
  shades, is to divide the image into pixels, the
  number depending on the required spatial
  resolution.
• The next step is to determine the number of
  brightness levels (shades of gray, from black to
  white) that we wish to represent, depending on
  the desired brightness resolution.
• If, for example we want 64 brightness levels,
  then we need to assign a 6 bit code for each
  pixel.
• Each pixel is examined, and its brightness level
  is rounded off to the closest brightness level
  out of the 64 levels that we have available
• As a result of this operation, each pixel now has
  a 6-bit number associated with it, representing
  the brightness level that is closest to the
  actual brightness level at that pixel.

20

• This process is known as quantization - (we will
  learn more about this later in the course) - it
  is the process of rounding off actual continuous
  values so that you end up with discrete
  information that can be represented by a finite
  number of bits.
• As a result of the operations just described, the
  analog image is digitized and represented by a
  string of binary digits

1010010101010101010
21
6-bit image (64 gray levels)
The effect of reducing the brightness resolution.

• In the figures below, each pixel in the image is
  represented by
• 6 bits, 3 bits and 1 bit. The spatial resolution
  is the same for
• all 3 pictures.

3-bit image (8 gray levels)
22
1-bit image (black and white)
23
How much storage is needed?

• Total number of bits required for storage total
  number of pixels number of bits used per pixel
• For example Black and white photo
• 64 x 64 pixels
• Use 32 gray levels (5 bits)
• 64 x 64 x 5 20,480 bits
• 20, 480 / 8 2,560 / 1024 bytes 2.5KB
• Remember data storage is in bytes
• KB represents 210 or 1024 bytes

24
Another example

• Black and White photo
• 256 x 256 pixel
• 6 bits (64 gray levels)
• How much storage is needed?
• 256 x 256 x 6 393,216 bits
• 393,216 / 8 49,152 bytes
• 49,152 / 1024 48 KB

25
Image Resolution - Summary

• Since the total number of bits required for
  storage total number of pixels number of bits
  used per pixel, there are two ways to reduce the
  number of bits needed to represent an image
• Reduce total number of pixels
• Reduce number of bits used per pixel
• Applying these however, reduces the quality of
  the image. The first results in low spatial
  resolution (image appears coarse). The second
  results in poor brightness resolution, as seen by
  the previous couple of slides.
• The amount of storage can, however be reduced by
  applying Image Compression techniques (discussed
  later).

26
Next Topic
Introduction to Information Technology

• Week 3

27
Overview

• Chapter 5 From the real world to Images and
  Video
• Digitizing Color Images
• Digital Video
• Chapter 8 Image Compression
• Lossless compression
• Lossy compression
• Chapter 9 Digital Video
• MPEG video compression

28
Digitizing Color Images

• Recall that any color can be created by adding
  the right proportions of red, green and blue
  light.
• If we wish to digitize a color image, we must
  first divide the image into pixels, again
  depending on the required spatial resolution.
• We must then examine each pixel, and determine
  the amount of red, green and blue (RGB) that is
  used to form the color at each pixel location.
• We must then round off these values to achieve
  the closest color on our color palette from among
  the different colors whose number depends on the
  desired brightness resolution.

29

• Finally, we must convert these three levels to a
  binary number of a predefined length.
• For example
• If we use 3 bits for each color value, we would
  be able to represent 8 intensity levels each of
  red, green and blue
• This representation would require 9 bits per
  pixel
• This would give us 512 different colors per pixel

30
Example how much storage

• Color photo
• 256 x 256 pixel
• 9 bits per pixel (3 bits each for red, green and
  blue)
• 256 x 256 x 9 589,826 bits
• 589,826/8 73,728 bytes
• 73,728/1024 72 KB of storage needed
  to store this color photo

31
Hue Luminance Saturation

• Another approach to color representation of
  images is Hue, Luminance and Saturation (HLS)
• This system does not represent colors by
  combinations of other colors, but it still uses 3
  numerical values
• Hue where the pure color component falls on a
  scale that extends across the visible light
  spectrum
• Luminance how light or dark a pixel is
• Saturation how pure the color is, i.e. how
  much it is diluted by the addition of white (100
  saturation means no dilution with white)

32
Video

• Human perception of movement is slow
• Studies show that humans can only take in 20
  different images (frames) per second before they
  begin to blur together
• If these images are sufficiently similar, then
  the blurring which takes place appears to the eye
  to resemble motion, in the same way we discern it
  when an object moves smoothly in the real world.
• We can detect higher rates of flicker, but only
  to about 50 per second
• This phenomenon has been used since the beginning
  of the 20th century to produce moving pictures,
  or movies.
• Movies show 24 frames (images) per second, but
  flash at 48 per second

33

• TV works similarly, but instead of a frame, TV
  refreshes in lines across the tube
• This same phenomenon can be used to create
  digitized video--a video signal stored in binary
  form
• We have already discussed how individual images
  are digitized digital video simply consists of a
  sequence of digitized still images, displayed at
  a rate sufficiently high to appear as continuous
  motion to the human visual system. The individual
  images are obtained by a digital camera that
  acquires a new image at a fast enough rate (say,
  60 times per second), to create a time-sampled
  version of the scene in motion
• Because of human visual latency, these samples at
  certain instants in time are sufficient to
  capture all of the information that we are
  capable of taking in!

34
Adding up the bits

• Assume a screen that is 512 x 512 pixels --
  about the same resolution as a good TV set.
• Assume 3 bits per color per pixel, for a total of
  9 bits per pixel
• Let's say we want the scene to change 60 times
  per second, so that we don't see any flicker or
  choppiness. This means we will need 512 x 512
  pixels x 9 bits per pixel x 60 frames per second
  x 3600 seconds 500 billion bits per hour --
  just for the video. Francis Ford Coppola's The
  Godfather, at over 3 hours, would require nearly
  178 GB of memory using this approach.
• But, do films actually require this much storage?
  No..
• The reason we can represent video with
  significantly fewer bits than in this example is
  due to compression techniques, which take
  advantage of certain predictabilities and
  redundancies in video information to reduce the
  amount of information to be stored.

35
Image Compression

• Near Photographic Quality Image
• 1,280 x 800 pixels, with 24 bits of color
  information per pixel
• Total 1280 x 800 x 24 24,576,000 bits
• 56 Kbps modem
• 56,000 bits/sec
• How long does it take to download? 24,576,000 /
  56,000 439 seconds/60 7.31 minutes

Obviously image compression is essential.
36
Image Compression

• Images are well suited for compression
• Images have more redundancy than other types of
  data.
• Images contain a large amount of structure.
• Human eye is very tolerant of approximation
  error.
• 2 types of image compression
• Lossless image compression
• Lossy image compression
• There is a tradeoff between image quality and
  degree of compression
• In lossless image compression, all the original
  data is restored upon decompression, but the
  amount of compression which can be achieved is
  not very high.
• In lossy image compression, some of the original
  data is lost, but a high degree of image
  compression can be achieved.
• Generally, the higher the degree of compression,
  the higher the data loss.
• A high degree of image compression is essential
  to reduce both download time and storage space

37
Lossless Image Compression

• Every detail of original data is restored upon
  decompression
• Examples Run Length Encoding, JPEG, GIF
• Run Length Encoding
• Used in an image format called PCX, commonly used
  in PCs
• Provides a small amount of compression
• Idea behind it is that if a long string of pixels
  are identical, then compression can be achieved
  by only sending a special code that represents
  that string of pixels
• e.g Instead of sending 111111111111111111111111,
  we can send the same information as 24 1s
• GIF
• Short for Graphics Interchange Format
• A commonly encountered compressed image format
• Provides a moderate amount of compression
• Developed by CompuServe, one of the first
  companies to provide telephone based computer
  network access
• Uses the Lempel-Ziv-Welch algorithm to compress
  data

38
Lossless Image Compression

• JPEG - Joint Photographic Experts Group
• One of the most commonly used image compression
  technique/standard
• Can provide high compression
• 29 distinct coding systems for compression, of
  which 2 are for Lossless compression
• Lossless JPEG uses a technique called predictive
  coding to attempt to identify pixels later in the
  image in terms of previous pixels in that same
  image

JPEG and GIF are the standard image formats on
the Web.
39
Lossy Image Compression

• Portion of original data is lost
• Degree of data loss depends on the degree of
  compression
• Good for images and audio
• Example JPEG
• Lossy JPEG relies on image simplification by
  removing image complexity at some loss of
  fidelity

40
Digital Video Compression (MPEG)
Motion Picture Expert Group (MPEG) standard for
video compression.

• MPEG is a series of techniques for compressing
  streaming digital information
• DVDs use MPEG coding
• MPEG achieves compression results on the order of
  1/35 of original
• If we examine two still images from a video
  sequence of images, we will almost always find
  that they are similar
• This fact can be exploited by transmitting only
  the changes from one image to the next. This is
  called Image Difference Coding
• Many pixels will not change from one image to the
  next.

41
Example

• Recall Godfather example - it required 178 GB of
  storage.
• With MPEG, this can be reduced to only a few GB,
  and stored in at most 2 DVDs.

42
Comments for next class

• Go over todays lecture notes
• Go over todays examples
• Read chapters 7, 6 (94-98), 3 error coding, and 4
• HW2 due next class
• Bring questions for discussion during review
  session