Media File Formats Jon Ivins, DMU

Text Files n Two types n 1. Plain text (unformatted) u ASCII Character set is most common u 7 bits are used u This can represent 128 Code words F A = F a=

Parity / Extended Character Sets n Computers store data in bytes n The extra bit can be used for: u Error detection F A parity bit is used F (Odd Parity) u Extend codewords to 256 F IBM’s EBCDIC

Text Files n 2. Formatted Text u Used by Word Processors / DTP F Characters used to give text and formatting information F Bold, Italic, Position, etc F Also contains information on page numbers, version, index, etc u Formatted files are usually much larger than their plain text equivalent

Graphics Files n Consist of objects n Contain data on size, position, colour n These are called VECTOR graphics n Use INTER-ALIASING to smooth lines

Image Files n Consist of PIXELS n A pixel is a small area of the screen n VGA displays are 640 X 480 u 480 lines of 640 pixels u This is pixels n Pixels contain data on colour n Greyscale uses one byte u Black = 0, White = 255

n Colour uses 3 Bytes n 1 for Red, 1 for Green and 1 for Blue (RGB) n 24 bits gives 16 million RGB combinations BUT n most monitors are usually at 256 colours

Bit Mapped Files n Graphics use a mathematical relationship to describe their position & size n A line might be described by its end points 0,0, 10,10 n Double the size the co-ordinates are simply doubled 0,0, 20,20 n Graphic objects are scaleable n Normally, graphics objects are saved as BMP files which are not scaleable

GIF Files n Image files hold a lot of data u Image files tend to be large files n To reduce storage space COMPRESSION techniques are used n One solution is RUN LENGTH ENCODING u Count the number of pixels that are the same u Decoder uses this count to copy the original pixel X times

GIF Files u Developed by Compuserve u Used for single or multiple images u Based on LZW compression F Lempel, Ziv invented original algorithm F Welch developed it further u Replaces multiple strings of data with a TOKEN…….. And a count value u LZW can give reasonable compression  50%

GIF Files n Decompression is fairly quick n Universal standard n Not optimised for image compression n UNISYS hold patent on LZW so there may be a problem with royalties

JPEG Files n Joint Photographic Experts Group n Uses a Fourier Transform technique to eliminate high frequency components in image n Uses several algorithms including run-length encoding n Can be lossy u blockiness u posterisation u ringing

Video Files n AVI ( Audio Visual Interleave) u Supported on all versions of Windows from 1995 F Almost all PC users can watch AVI files F MAC users probably won’t be able to watch AVI files u Large file size ( 20 Mbytes per second)

MPEG n Motion Pictures Expert Group n Popular format u Good compression u Still large files n Uses similar compression techniques to JPEG

Other Video Formats n MOV u Mac format F can be difficult to play on PCs n Real Audio & Shockwave u “Streaming” files F Optimised for the Internet

Sound Files n Two main types n WAV files u Digital samples of analogue waveforms n Midi Files u Set of instructions to control computer

WAV Files n Sound is sampled according to Nyquist Sampling Theorem n SAMPLE RATE = 2 X Highest frequency n Telephone bandwidth is Hz u Sampling rate is 6800 times a second n Audio is , 000 Hz u Sampling rate is 40,000Hz

n We also need control information so sampling rate is always higher than the Nyquist limit n telephone speech is 8kHZ n CD Audio is approx.. 44kHZ n The better the frequencies the higher the sampling rate so the higher the quality

The sound is sampled at regular intervals

Conversion to digital n There are 21 signal levels u -10 to 0 to +10 n We need 5 bits to represent this range n Note 5 bits gives 32 combinations u Use 0XXXX for Positive values u Use 1XXXX for negative values

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Quantisation noise n The example uses a 1 volt step range n What if the audio sample is 7.5 volts? n The encoder gives a value of 8 volts n The decoder outputs an 8 volt signal n This error is called QUANTISATION NOISE

Companding n Most audio signals are quiet u more signals at lower levels than high levels n Companding means using a non-linear scale u For example, 0-5 volts might have 20 values u 5- 8 volts might have 8 values u 8-10 volts might have 2 values n This gives better resolution at lower levels at the expense of high signal levels

CD Quality WAV files n Use 16 X 2 bits to represent the audio signal n This gives X 2 “steps” u Quantisation noise is low u A lot of bits will carry no information (low sound levels) u This means a lot of data redundancy u WAV file size becomes large u 1Mbyte = 0.7 seconds of sound

MIDI Files n These are digital sound files n Control computers, sequencers, etc n Each bit in the signal is used n Must have a MIDI player to hear the sound n File size is very small compared to WAV files

Audio Compression n ADPCM u Predicts next sample value n TrueSpeech u Based on mathematical model of airflow over vocal tract u Highly efficient (1/16th) n MPEG Audio u Fits with MPEG Video files

Zip Files n Popular file compression utility u Based on LZW n Used to transfer or store large files n Zipped files give good results for text and WAV files n Poor results for graphics / video (typically 3%)

File Size / Performance n There is a trade-off between: Speed of loading File size Quality n There is no one correct solution for all multimedia applications