1. UCB Source Coding Jean Walrand EECS

2. UCB Outline Compression Losless: Huffman Lempel-Ziv Audio: Examples Differential ADPCM SUBBAND CELP Video: Discrete Cosine Transform Motion Compensation

3. UCB Compression Goal: Reduce the number of bits to encode source Lossless: For data Lossy: For voice, video Approaches:

4. UCB Huffman Encoding Lossless Key Idea: Use shorter code words for more frequent symbols EX1:

5. UCB Huffman Encoding (continued) EX2:

6. UCB Huffman Encoding (continued) If the symbols are independent and identically distributed, the Huffman encoding is the prefix-free code with the minimum average number of bits. Note: The Shannon encoding requires fewer bits, but requires encoding large blocks of symbols. Both codes assume that the distribution is known.

7. UCB Lempel-Ziv Lossless Symbols are not independent Distribution is not known Want to minimize the average number of bits Typical application: any file Approach: Build dictionary and replace string with location of prefix in the dictionary

8. UCB Lempel-Ziv (continued) Example:

9. UCB Audio Examples: Speech: PCM 64kbps ADPCM32-64kbps SBC16-32kbps VSELP-CELP2.4-8kbps Audio: PCM1400kbps MPEG48-384kbps

10. UCB Audio (c’d) Differential Encoding (also used for Video): Key Idea is that differences between successive samples may be small Difficulty: Error Propagation

11. UCB Audio (c’d) Differential Encoding (c’d)

12. UCB Audio (c’d) ADPCM: Adaptive Differential PCM Predict next value, encode error

13. UCB Audio (c’d) Sub-Band Coding: Improves performance

14. UCB Audio (c’d) CELP (Code Excited Linear Predictor)

15. UCB Video Discrete Cosine Transform Objective: Extract “Visible Information” f(x, y) =  m,n F(m, n) cos(mx) cos(ny)

16. UCB Video (cd) Motion Compensation Idea: Track motion of picture Encode (motion vector, modification)