Multimedia Data Compression

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Multimedia Data Compression

• Mee Young Sung
• University of Incheon
• Department of Computer Science Engineering
• mysung_at_incheon.ac.kr

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1. Lossless Compression Algorithms
2. Introduction
3. Basics of Information Theory
4. Run-Length Coding
5. Variable-Length Coding(VLC)
6. Shannon-Fano Algorithm
7. Huffman Coding
8. Adaptive Huffman Coding
9. Dictionary-Based Coding
10. Arithmetic Coding
11. Lossless Image Compression
12. Differential Coding of Images
13. Differential Coding of Images
14. Lossless JPEG

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• Lossy Compression Algorithms
• Introduction
• Distortion Measures
• The Rate-Distortion Theory
• Quantization
• Uniform Scalar Qunantization
• Nonuniform Saclar Qunantization
• Vector Qunantization
• Quantization
• Discrete Cosine Transform(DCT)
• Karhunen-Loève Transform
• Wavelet-Based Coding
• Introduction
• Continuous Wavelet Transform
• Discrete Wavelet Transform
• Wavelet Packets
• Embedded Zerotree of Wavelet Coefficients
• The Zerotree Data Structure
• Successive Approximation Quantization

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• Image Compression Standard
• The JPEG Standard
• Main Steps in JPEG Image Compression
• JPEG Modes
• A Glance at the JPEG Bitstream
• The JPEG2000 Standard
• Main Steps of JPEG2000 Image Compression
• Adapting EBCOT to JPEG2000
• Region-of-Interest Coding
• Comparison of JPEG and JPEG2000 Performance
• The JPEG-LS Standard
• Prediction
• Context Determination
• Residual Coding
• Near-Lossless Mode
• Bilevel Image Compression Standard
• The JBIG Standard
• The JBIG2 Standard

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• Basic Video Compression Techniques
• Introduction to Video Compression
• Video Compression Based on Motion Compensation
• Search for Motion Vectors
• Sequential Search
• 2D Logarithmic Search
• Hierarchical Search
• H.261
• Intra-Frame (I-Frame) Coding
• Inter-Frame (P-Frame) Predictive Coding
• Quantization in H.261
• H.261 Encoder and Decoder
• A Glance at the H.261 Video Bitstream Syntax
• H.263
• Motion Compensation in H.263
• Optional H.263 Coding Modes
• H.263 and H.263

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• MPEG Video Coding I MPEG-1 and 2
• Overview
• MPEG-1
• Motion Compensation in MPEG-1
• Other Major Differences form H.261
• MPEG-1 Video Bitstream
• MEPG-2
• Supporting Interlaced Video
• MPEG-2 Scalabilities
• Other Major Differences form MPEG-1

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• MPEG Video Coding II MPEG-4, 7, and Beyond
• Overview of MPEG-4
• Object-Based Visual Coding in MPEG-4
• VOP-Based Coding vs. Frame-Based Coding
• Motion Compensation
• Texture Coding
• Shape Coding
• Static Texture Coding
• Sprite Coding
• Global Motion Compensation
• Synthetic Object Coding in MPEG-4
• 2D Mesh Object Coding
• 3D Model-based Coding
• MPEG-4 Object Types, Profiles and Levels
• MPEG-4 Part10/H.264
• Core Features
• Baseline Profile Features
• Main Profile Features
• Extended Profile Features

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• Basic Audio Compression Techniques
• ADPCM in Speech Coding
• ADPCM
• G.726 ADPCM
• Vocoders
• Phase Insensitivity
• Channel Vocoder
• Formant Vocoder
• Linear Predictive Coding
• CELP
• Hybrid Excitation Vocoders

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• MPEG Audio Compression
• Psychoacoustics
• Equal-Loudness Relations
• Frequency Masking
• Temporal Masking
• MPEG Audio
• MPEG Layers
• MPEG Audio Strategy
• MPEG Audio Compression Algorithm
• MPEG-2 AAC(Advanced Audio Coding)
• MPEG-4 Audio
• Other Commercial Audio Codecs
• The Future MPEG-7 and MPEG-21

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Run-Length Coding

• ???
• 00 ... 00100 ... 001100 ... 00100
  ... 001100 ... 00 89 ??
•                     ?      
  ?                       
• 0??????  14        9        20       
  30         9
•                                   0????           
           0????
• ???? ???? ??
• Run length(??) 1110 1001 0000 1111 0101 1111 1111
  0000 0000 1001 40??
• Run length(??)  14     9    0     15   
  5   15    15    0     0    9    

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Huffman Coding

• Encoding for Huffman Algorithm
• A bottom-up approach
• 1. Initialization Put all nodes in an OPEN list,
  keep it sorted at all times (e.g., ABCDE).
• 2. Repeat until the OPEN list has only one node
  left
• (a) From OPEN pick two nodes having the lowest
  frequencies/probabilities, create a parent node
  of them. (b) Assign the sum of the children's
  frequencies/probabilities to the parent node and
  insert it into OPEN. (c) Assign code 0, 1 to the
  two branches of the tree, and delete the children
  from OPEN.

Symbol Count log2(1/pi) Code Subtotal ( of bits)
A 15 1.38 0 15
B 7 2.48 100 21
C 6 2.70 101 18
D 6 2.70 110 18
E 5 2.96 111 15

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Huffman Coding

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  ??? ? ??
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Fourrier Transform
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Reinforcement and Interference
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Complex Wave Fundamental and Spectral Frequencies
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Line Spectrum
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Fundamental Frequency in a Line Spectrum
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DCT

• Discrete Cosine Transform (DCT)
• Inverse Discrete Cosine Transform (IDCT)

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Example 1
1D DCT
1D IDCT
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Example 2
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Example 3
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Example 4
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Example of 1D IDCT(Inverse DCT)
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JPEG

• Joint Photographic Expert Group
• Motivation
• The compression ratio of lossless methods (e.g.,
  Huffman, Arithmetic, LZW) is not high enough for
  image and video compression, especially when the
  distribution of pixel values is relatively flat.
• JPEG uses transform coding, it is largely based
  on the following observations
• Observation 1 A large majority of useful image
  contents change relatively slowly across images,
  i.e., it is unusual for intensity values to alter
  up and down several times in a small area, for
  example, within an 8 x 8 image block. Translate
  this into the spatial frequency domain, it says
  that, generally, lower spatial frequency
  components contain more information than the high
  frequency components which often correspond to
  less useful details and noises.
• Observation 2 Pshchophysical experiments suggest
  that humans are more receptive to loss of higher
  spatial frequency components than loss of lower
  frequency components.

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JPEG (DCT)

• Discrete Cosine Transform (DCT)
• Inverse Discrete Cosine Transform (IDCT)

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JPEG

• Encoding

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JPEG

• Major Steps
• DCT (Discrete Cosine Transformation)
• Quantization
• Zigzag Scan
• DPCM on DC component
• RLE on AC Components
• Entropy Coding

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JPEG (DCT)

• The 64 (8 x 8) DCT basis functions

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JPEG (DCT)

• Computing the DCT
• Factoring reduces problem to a series of 1D DCTs

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JPEG (Quantization)

• F'u, v round ( Fu, v / qu, v ). Why? --
  To reduce number of bits per sample
• Example 101101 45 (6 bits). qu, v 4 --gt
  Truncate to 4 bits 1011 11.
• Quantization error is the main source of the
  Lossy Compression.
• Uniform Quantization
• Each Fu,v is divided by the same constant N.
• Non-uniform Quantization -- Quantization Tables
• Eye is most sensitive to low frequencies (upper
  left corner), less sensitive to high frequencies
  (lower right corner)
• The numbers in the above quantization tables can
  be scaled up (or down) to adjust the so called
  quality factor.
• Custom quantization tables can also be put in
  image/scan header.

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JPEG (Quantization)

• The Luminance Quantization Table q(u, v)
  The Chrominance Quantization Table q(u, v)

Eye Sensitivity
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JPEG (Zig-Zag Scan)

• Zig-zag Scan
• Why? -- to group low frequency coefficients in
  top of vector.
• Maps 8 x 8 to a 1 x 64 vector

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JPEG (DPCM on DC component )

• DPCM (Differential Pulse Code Modulation)
• DC component is large and varied, but often close
  to previous value.
• Encode the difference from previous 8 x 8 blocks
  DPCM
• DPCM ???/??? ?
• ??? ????? ????? ????? ?? ???, ?? ?? ??? ????? ?
  ??? ??? ???? ????? ??

(a)??? ??? ??? 14 19 25 36 43 55 66 52 48 34
(b) DPCM??? ??? 14 5 6 11 7 12 11 -14 4 -14
(c)??? ??? 14 19 25 36 43 55 66 52 48 34
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JPEG (RLE on AC components )

• RLE (Run Length Encode)
• 1 x 64 vector has lots of zeros in it
• Keeps skip and value, where skip is the number of
  zeros and value is the next non-zero component.
• Send (0,0) as end-of-block sentinel value
• Zig-Zag scanned ACs

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JPEG (Entropy Coding )

• Categorize DC values into SIZE (number of bits
  needed to represent) and actual bits.
• Example if DC value is 4, 3 bits are needed.
• Send off SIZE as Huffman symbol, followed by
  actual 3 bits.
• For AC components two symbols are used Symbol_1
  (skip, SIZE), Symbol_2 actual bits. Symbol_1
  (skip, SIZE) is encoded using the Huffman coding,
  Symbol_2 is not encoded.
• Huffman Tables can be custom (sent in header) or
  default.

Size Amplitude 0 0 1 -1,1 2 -3,-2,2,3 3
-7,-6,-5,-4,4,5,6,7
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• http//www.cs.sfu.ca/mmbook/demos.htm
• http//www.cs.sfu.ca/CC/365/li/material/misc/demos
  .html