1. Digital Representations Digital Video Special Effects Fall 2006

2. Analog-to-Digital (A-D) Conversion Sampling Quantization Coding

3. Sampling -- Analog to Discrete Analog signal to discrete-time signal x(t) --> x[n] Sampling procedure f(t) is the sampling function Simple sampling x[n] = x(t=n), i.e., f(t)=  (t)

4. Reconstruction: Discrete to Analog Can we reconstruct analog signal from its discrete time samples? x[n] --> x(t) ? Generally not. Nyquist (Shannon) sampling theorem for bandlimited signals If the simple sampling rate is at least twice bandwidth of the analog signal, the analog signal can be perfectly reconstructed:

5. Quantization -- Digitization Discrete-time signal  digital signal Quantization error Quantization level How many bits to represent one sample? Trade-off between error and bit rate (communication band width) Nonlinear quantization Pre-compression and de-compression (  law and A law) Vector quantization

6. Raw Data Rate Sampling frequency= f (Hz) Each sample represented by R bits Raw data rate (bit rate): T = f x R (bits per second, or bps)

7. Digital Audio Signals Frequency band of sound: human hearing frequency range: 20Hz-20 KHz. Sampling rate > 40 KHz (Actual sampling rate of CD-Audio = 44.1 KHz) Bit rate for CD quality audio signal (44.1 KHz, Quantization:16 bits, 2 channels): T = 44100 x 16 x 2 (bits per second, or bps) CD quality stereo sound  10.6 MB / min

8. Examples

9. Speech Signals Properties Human ear: most sensitive to 600Hz-6000Hz Quasi-stationary for around 30 ms Characteristic maxima -- formants Speech analysis and synthesis Speech components, e.g., vowels and consonants

10. MIDI A protocol that enables computer, synthesizers, keyboards, and other musical device to communicate with each other. Bit rate: 31.25Kbps A MIDI file stores the messages regarding specific musical actions. Commands, instead of actual waveforms, are saved. One minute of MIDI: 4KB storage.

11. Digital Image Representation Picture elements (pixels) Sampling, quantization Higher dimensional image -- voxels Bi-level images (black/0 or white/1) Grayscale images 1 byte/pixel: 256 gray levels Color images True color: RGB 24bits/pixel Image size, e.g. VGA 640x480 Grayscale image: 307,200 bytes True color image: 921,600 bytes

12. Graphics Format Graphics primitives and attributes 2-D objects: lines, rectangles, circles, ellipses, text strings, etc. Attributes: line style, line width, color, etc. High-level representation: structured, object- based Low-level representation: bitmap

13. Computer Graphics Computer animation Computer Generated Images (CGI) Photo-realistic rendering

14. Video Signal Requirements Aspect ratio: TV  4/3; HDTV  16/9 Luminance and chrominance Continuity of motion > 15 frames/s TV 30 or 25 frames/s, movie 24 frames/s Flicker. Marginal at least 50 refresh cycles/s Movie: 2x24=48 TV: Half picture by line-interleaving Scanning rate: at lease 25Hz, finish one frame in 1/25s

15. Color Representation in Video RGB, normalized R=G=B=1 -- white color YUV signal Y=0.30R+0.59G+0.11B (Luminance) U=(B-Y) x 0.493, V=(R-Y) x 0.877 (Chrominance channels) Example: PAL, CD-I and DVI (Digital Video Interactive) video. YIQ signal Y=0.30R+0.59G+0.11B (Luminance) I=0.60R-0.28G-0.32B, Q=0.21R-0.52G+0.31B Example: NTSC Avoid cross talk between luminance and colors: S-Video video signals separate the luminance and chrominance information into two separate analog signals.

16. Subsampling in Video Different spatial sampling rates for different chrominance channels Human beings are more sensitive to luminance (using more samples) while less sensitive to colors (using less samples). Different resolution for different components Y:C1:C2 -- 4:2:2 Subsampling and upsampling techniques

17. Computer Video Format CGA (Color Graphics Adapter): 4 colors, 320x200x2bits = 16,000 bytes EGA: 640x350x4bits = 112,000 bytes VGA: 640x480x8bits = 307,000 bytes SVGA: 800x600 pixels XGA: 1024x768 pixels SXGA: 1280x1024 pixels

18. Video Quality VCR Quality -- SIF (MPEG1) NTSC: 240x352; PAL: 288x352 per frame Videoconferencing quality CIF (Common Interchange Format) -- H.261 288x352, subsampling 4:1:1(halving both direction) Q: what is the raw bit rate of CIF video (30frames/s)? QCIF (Quarter CIF) 144x176, subsampling 4:1:1(halving both direction) Q: what is the raw bit rate of QCIF video (30frames/s) Super-CIF: 576x704, subsampling 4:1:1(halving both direction)

19. The Need for Compression Take, for example, a video signal with resolution 320x240 and 256 (8 bits) colors, 30 frames per second Raw bit rate = 320x240x8x30 = 18,432,000 bits = 2,304,000 bytes = 2.3 MB A 90 minute movie would take 2.3x60x90 MB = 12.44 GB Without compression, data storage and transmission would pose serious problems!

20. Data Compression Data compression requires the identification and extraction of source redundancy. In other words, data compression seeks to reduce the number of bits used to store or transmit information.

21. Lossless Compression Lossless compression can recover the exact original data after compression. It is used mainly for compressing database records, spreadsheets or word processing files, where exact replication of the original is essential. Examples: Run Length Encoding (RLE), Lempel Ziv Welch (LZW), Huffman Coding.

22. Lossy Compression Result in a certain loss of accuracy in exchange for a substantial increase in compression. More effective when used to compress images and voice where losses outside visual or aural perception can be tolerated. Most lossy compression techniques can be adjusted to different quality levels. Example: DCT(JPEG), MPEG

23. Compression Ratio Compression ratio original data size ------------------------- : 1 compressed data size