Digital Media Dr. Jim Rowan ITEC 2110-01 Monday, August 27.
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Transcript of Digital Media Dr. Jim Rowan ITEC 2110-01 Monday, August 27.
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Digital Media
Dr. Jim Rowan
ITEC 2110-01
Monday, August 27
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Roll Call using Banner
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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
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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
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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
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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
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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
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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
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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
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From the Real Worldto
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)
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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
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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
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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
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[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) TextAudioImageVideo
(open and crop jayley and manOfScience)
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Note on paper
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Picture
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Song: fieldsOfGold.mp3
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Video
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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
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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
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Digital back to the real world:– Display samples using “sample and hold”– Play the sample for the duration of the
sample time
Converting Discrete data back to
Continuous (analog) data
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But... How many samples?
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single sample
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single sample
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two samples
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two samples
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three samples
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three samples
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four samples
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four samples
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five samples
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five samples
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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
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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
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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)
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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...
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FieldsOfGold.mp3
• Why 26.3 megabytes not 1.2 megabytes?
• This is an MP3!
• Data COMPRESSION!
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Undersampling & VideoRetrograde Motion
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Further reading
• http://en.wikipedia.org/wiki/Nyquist_rate
• http://en.wikipedia.org/wiki/Sampling_%28signal_processing%29
• http://en.wikipedia.org/wiki/Mp3
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Questions?
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