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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

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cis679 multimedia basics
CIS679: Multimedia Basics
  • Multimedia data type
  • Basic compression techniques
multimedia data type
Multimedia Data Type
  • Audio
  • Image
  • Video
audio
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
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
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
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
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
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
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
entropy encoding techniques
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
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
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
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
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
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
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