Transcript ITEC2110-04August28.ppt

Digital Media
Dr. Jim Rowan
ITEC 2110-01
Monday, August 27
Roll Call using Banner
File formats and extensions
• Indication to us (the humans) what kind
of file this is
• Some software looks at the extension
– so... some software will try to open files
with improper extensions
– results in “file corrupted” error message
– try it... change the extension from .doc to
.jpg
File formats and extensions
• Some software looks at the data in the file for
more definitive answer
– important file-related information is encoded in the
data of the file
• for example: some image formats have color tables to
reduce the size of the file
• some video just saves the changes from one frame to the
next
Numbering systems
• Humans: decimal
– Humans: 10 fingers, 10 digits:
– 0, 1, 2, 3, 4, 5, 6, 7, 8 & 9
• Computers: binary
– Computers: 2 fingers, 2 digits
–0&1
Binary Coding
• Data for a computer
– zeros and ones,
– off and on
– false and true
• Data for humans
– Coding schemes are used by humans to reduce
the volume of digits
– Two coding schemes used
• Hexadecimal
• ASCII
Hexadecimal
• Humans and Computers: hexadecimal
– Hexadecimal: 16 fingers, 16 digits
– Humans organize 0s and 1s into groups of 4
– These groups of 4 are can be represented by a
single hexadecimal digit
– 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E, F
ASCII
• Humans and Computers: ASCII
– Made of two hexadecimal codes
– One ASCII character - two hex codes
– ASCII code for R (from text pg 317)
• hexadecimal: 52
• binary: 0101 0010
How to count using a different
number of fingers
• 10 fingers: Counting in decimal
– 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
– start over but put a 1 in the higher position
• 2 fingers: Counting in binary
– 0, 1
– start over but put a 1 in the higher position
• 16 fingers: Counting in hexadecimal
– 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E, F
– start over but put a 1 in the 1 higher position
From the Real World
to
Stuff on a computer
• A note
– Paper and pen -> bits (0s and 1s)
• A picture
– Reflected light -> bits (0s and 1s)
• A song
– Pressure waves in air -> bits (0s and 1s)
• A video
– Pressure waves in air and Reflected light ->
bits (0s and 1s)
Phenomena in the Real world:
discrete vs continuous
•
•
•
•
Things in the real world can be discrete
They either ARE or ARE NOT there
These things can be counted
Examples:
– The number of cars in the parking lot
– The number of beans in a jar
Phenomena in the Real world:
discrete vs continuous
• Things in the real world can be continuous
• Continuous can’t be counted, it must be
measured
• Examples:
– Atmospheric pressure
– Height of an ocean wave
– Frequency of a sound wave
But...
computers can only count
• Discrete data is easy for a computer
– count it and store it as a number
• Continuous data... not so much
– music:
• measure the frequency & amplitude
• encode as discrete
– pictures:
• measure the amount of light and its color
• encode as discrete
[Switch to Mac]
Play/show some stuff
Text (using Text Edit)
Audio (using Quicktime)
Image (using Preview)
Video (using Quicktime)
Open same stuff (using HexFiend)
Text
Audio
Image
Video
(open and crop jayley and manOfScience)
Note on paper
Picture
Song: fieldsOfGold.mp3
Video
Question...
• Computers only store 0s and 1s
– They only store digits...
• So...
• How does all this continuous stuff end up in a
computer so that we can save it and play it
back?
• Continuous data must be converted to
discrete data
Converting
Continuous (analog) data
to Discrete data
• Requires two processes
– sampling - equally spaced
– quantization - measuring at each sample
• Usually handled by
– analog to digital converter
– AKA A to D converter or ADC
Converting Discrete data
back to
Continuous (analog) data
Digital back to the real world:
– Display samples using “sample and hold”
– Play the sample for the duration of the
sample time
But... How many samples?
single sample
single sample
two samples
two samples
three samples
three samples
four samples
four samples
five samples
five samples
How frequently should I
sample?
• too few
– small file size (good)
– not a faithful representation when replayed
• too many
– large file size (bad)
– excellent representation when replayed
• The Nyquist rate
– twice as many samples as the frequency
– ok file size
– faithful representation when replayed
Nyquist rate
• Why is the sample size used for audio CDs
44,000 samples per second?
– Human hearing response is in the range of 0 to
22,000 cycles per second
• Why is the sample size used for audio CDs
44,000 samples per second?
– Human hearing response is in the range of 0 to
22,000 cycles per second
FieldsOfGold.mp3
• 4 minutes and 59 seconds long
• 1,201,173 bytes in length
Does this make sense?
• 4 minutes and 59 seconds long
– 299 seconds
• 44,000 samples per second (sample rate)
• 16 bit samples (quantity stored for each
sample)
FieldsOfGold.mp3
• 4’59 = 299 seconds long
• 299 x 44,000 samples per second
= 13,156,000 bytes
• 13,156,000 x 2 bytes/sample
– 26,312,000 bytes
• Should be 26.3 megabytes!
• Why only 1.2 megabytes?
• HMMMmmm...
FieldsOfGold.mp3
• Why 26.3 megabytes not 1.2 megabytes?
• This is an MP3!
• Data COMPRESSION!
Undersampling & Video
Retrograde Motion
Further reading
• http://en.wikipedia.org/wiki/Nyquist_rate
• http://en.wikipedia.org/wiki/Sampling_%
28signal_processing%29
• http://en.wikipedia.org/wiki/Mp3
Questions?