CIS679: Multimedia Basics
 Multimedia data type
 Basic compression techniques
Multimedia Data Type
 Audio
 Image
 Video
Audio
 Digitization
 Sampling
 Quantization
 Coding
 Higher sampling rate -> higher quality
 Nyquist sampling theorem: for lossless digitization, the
sampling rate should be at least twice the maximum
frequency responses
 Higher bits per sample -> higher quality
 Sampling at 8 KHz, 8 bit samples -> 64kbits/sec
 CD-quality audio
 Sampling at 44.1KHz, 16 bit samples -> 705.6 kbits/sec
Image/Video
 Digitization
 Scan a picture frame
 Digitize every pixel
 Color represented by RGB
 Normally converted to Y (black and white TV), U
and V


Luminance Y = 0.30R + 0.59G + 0.11 R
Chrominance U = (B-Y) * 0.493
V = (R-Y) * 0.877
Video Transmission Standards
 NTSC
 Y = 0.30R + 0.59G + 0.14B
 I = 0.60R + 0.28G + 0.32B
 Q = 0.21R + 0.52G + 0.21B
 PAL
Studio-quality TV
 NTSC
 525 lines at 30 frames/second
 Y sampled at 13.5 MHz, Chrominance values at 6.75 MHz
 With 8-bit samples,
 Data rate = (13.5 + 6.75 + 6.75) * 8 = 216 Mbps
Summary of Multimedia Data Types
 Audio data rate = 64kbps, and 705.6kbps
 Video date rate = 216 Mbps
 Compression is required!
Can Multimedia Data Be Compressed?
 Redundancy can be exploited to do compression!
 Spatial redundancy
 correlation between neighboring pixels in image/video
 Spectral redundancy
 correlation among colors
 Psycho-visual redundancy
 Perceptual properties of human visual system
Categories of Compression
 Lossless
 No distortion of the original content
 Used for computer data, medical images, etc.
 Lossy
 Some distortion
 Suited for audio and video
Compression Techniques
Run-length Coding
Entropy
Encoding
Huflfman Coding
Arithmetic Coding
DPCM
Prediction
DM
FFT
Transformation
DCT
Source Coding
Bit Position
Layered Coding
Subsampling
Sub-band Coding
Vector Quantization
J PEG
MPEG
Hybrid Coding
H.261
DVI RTV, DVI PLV
Entropy Encoding Techniques
 Lossless compression
 Run-length encoding
 Represent stream as (c1, l1), (c2, l2),…, (ck, lk)
 1111111111333332222444444 = (1, 10) (3, 5) (2,4) (4, 5)
 Or ABCCCCCCCCDEFGGG = ABC!8DEFGGG
 Pattern Substitution
 Substitute smaller symbols for frequently used patterns
Huffman Coding
 Use variable length codes
 Most frequently used symbols coded with fewest
bits
 Codes are stored in a codebook
 Codebook transferred with the compressed
stream
Source Encoding Techniques
 Transformation encoding
 Transform the bit-stream into another domain
 Data in the new domain more amenable to compression
 Type of transformation depends on data
 Image/video transformed from time domain into
frequency domain (DCT)
Differential/Predictive Encoding
 Encoding the difference between actual value and
a prediction of that value
 Number of Techniques



Differential Pulse Code Modulation (DPCM)
Delta Modulation (DM)
Adaptive Pulse Code Modulation (APCM)
 How they work?
 When consecutive change little
 Suited for audio and video
Vector Quantization
 Divide the data stream into blocks or vectors
 One or two dimensional blocks
 Use codebooks
 Find the closest symbol in codebook for a given
sample
 Transmit the reference to that symbol
 Codebook present at sender/receiver
 When no exact match, could send the error

Lossy or lossless
 Useful with known signal characteristics
 Construct codebooks that can match a wide range
of symbols
Major Steps of Compression
 Preparation
 Uncompressed analog signal -> sampled digital form
 Processing
 Source coding
 DCT typically used: Transform from time domain ->
frequency domain
 Quantization
 Quantize weights into integer codes
 Could use different number of bits per coefficient
 Entropy encoding
 Lossless encoding for further compression
Conclusion
 Multimedia data types
 Why multimedia can be compressed?
 Categories of compression
 Compression techniques
 Entropy encoding
 Source encoding
 Hybrid coding
 Major steps of compression
 What’s next?
 JPEG
 MPEG