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Digital Media

Digital Media. Dr. Jim Rowan Chapter 2. Roll Call using Banner. Project 1 preliminary. Details to be posted on the class projects page Podcast using Audacity Import music Do a voice-over Post the result on your wiki site. The Question:. How do you put stuff in a computer

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Digital Media

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  1. Digital Media Dr. Jim Rowan Chapter 2

  2. Roll Call using Banner

  3. Project 1 preliminary • Details to be posted on the class projects page • Podcast using Audacity • Import music • Do a voice-over • Post the result on your wiki site

  4. The Question: • How do you put stuff in a computer • so that you can manipulate it • so that you can send it • so that someone else can see and use it? • How do you represent the real world in a digital world?

  5. The answer: • Represent the real world as numbers • Store the numbers • Retrieve the numbers • Display them in a form humans understand

  6. Today: • Chapter 2 is a “first cut” of nearly all the material that will be covered in greater detail this semester • About the real world • About digital representationa

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. From the Real WorldtoStuff 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)

  15. 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

  16. 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

  17. 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

  18. [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)

  19. Note on paper

  20. Picture

  21. Song: fieldsOfGold.mp3

  22. Video

  23. 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

  24. Converting Continuous (analog) datato 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

  25. Converting Discrete data back toContinuous (analog) data Digital back to the real world: • Display samples using “sample and hold” • Play the sample for the duration of the sample time

  26. But... How many samples?

  27. single sample

  28. single sample

  29. two samples

  30. two samples

  31. three samples

  32. three samples

  33. four samples

  34. four samples

  35. five samples

  36. five samples

  37. 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

  38. 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

  39. 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)

  40. 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...

  41. FieldsOfGold.mp3 • Why 26.3 megabytes not 1.2 megabytes? • This is an MP3! • Data COMPRESSION!

  42. Undersampling & Video Retrograde Motion

  43. Further reading • http://en.wikipedia.org/wiki/Nyquist_rate • http://en.wikipedia.org/wiki/Sampling_%28signal_processing%29 • http://en.wikipedia.org/wiki/Mp3

  44. Sampling Artifacts • Under-sampling (too few samples) of continuous data can produce undesired artifacts • audio distortion • jagged edges on images • Moire’ patterns on images • retrograde motion on video

  45. Sampling Artifacts (cont.) • Not enough quantization levels when sampling continuous data can produce undesired artifacts • Images • too few color: colors look artificial • loss of fine distinction • too few grey levels: gradients become steps • too few brightness levels: posterization

  46. Sampling Artifacts (cont.) • Not enough quantization levels when sampling continuous data can produce undesired artifacts • Audio • too few amplitude levels, quantization noise - hiss • 8 bits (256 amplitude levels) produces discernable noise • 16 bits (65536 amplitude levels) CD quality, no discernable hiss • general sound “fuzziness”

  47. Multimedia Hardware Requirements • Multimedia consumption? • requires only a lower powered machine • Multimedia production? • requires a more powerful computer • consider “fields of gold.mp3” • 26+megabytes of data uncompressed • 1.2 megabytes of data compressed • images are produced in layers • then flattened for consumption

  48. Hardware requirements • Video capture requires large areas of contiguous disk space • Frequent disk defragmentation is required • http://en.wikipedia.org/wiki/Defragmentation

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