Digital Media Dr. Jim Rowan ITEC 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:

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

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

But... How many samples?

single sample

two samples

three samples

four 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 signal_processing%29

Questions?