1. Copyright 1998, S.D. Personick. All Rights Reserved1 Telecommunications Networking I Lectures 2 & 3 Representing Information as a Signal

2. Copyright 1998, S.D. Personick. All Rights Reserved2 Information and Signals Sound: speech, audio Images: character mapped, scanned, bit mapped, transform representations Video: frame-by-frame, compression

3. Copyright 1998, S.D. Personick. All Rights Reserved3 Capturing Sound

4. Copyright 1998, S.D. Personick. All Rights Reserved4 Capturing Sound Sound takes the physical form of an acoustic wave... variations in pressure vs time and space... that travels through a compressible physical medium such as air A microphone (transducer) converts locally received pressure variations into a varying voltage/current that represents the sound

5. Copyright 1998, S.D. Personick. All Rights Reserved5 Capturing Sound (cont’d) The varying voltage waveform that represents the captured sound is communicated to another location using one of many possible communication system technologies The received varying voltage waveform is not an exact replica of the transmitted voltage waveform

6. Copyright 1998, S.D. Personick. All Rights Reserved6 Capturing Sound (cont’d) The received varying voltage waveform is used to “drive” a speaker (transducer) which produces a new acoustic wave (sound) that is perceived as an approximation of the original sound Does the reproduced acoustic wave “sound” like the original acoustic wave? The answer depends upon the application

7. Copyright 1998, S.D. Personick. All Rights Reserved7 Representing Speech

8. Copyright 1998, S.D. Personick. All Rights Reserved8 Representing Speech (cont’d) Speech is one of the most important analog signals Representation qualities include: -Intelligibility: Can I understand what you are saying? Can I build a machine that responds properly to what you are saying? -Naturalness: Does it sound like face-to- face communication? -Comfort: Is it pleasant to listen to?

9. Copyright 1998, S.D. Personick. All Rights Reserved9 Representing Speech (cont’d) Traditional telephone quality speech: 3 kHz high frequency cutoff small amounts of noise and echo AM radio quality speech: 5 kHz high frequency cutoff varying amounts of noise and interference FM radio, TV, other high quality speech: 10 kHz+ high frequency cutoff

10. Copyright 1998, S.D. Personick. All Rights Reserved10 Representing Speech (cont’d) Compressed speech -Uses digital signal processing to remove redundancies in the original speech signal. -This typically impacts on the naturalness and comfort associated with the speech signal produced at the receiving end of a link, but (hopefully) still provides intelligibility

11. Copyright 1998, S.D. Personick. All Rights Reserved11 Representing Audio Audio signals, like music, typically demand a high accuracy of representation to meet users’ expectations >10 kHz high frequency cutoff <100 Hz low frequency cutoff low noise and distortion A typical audio system specification includes a 20-20,000 Hz “frequency response”

12. Copyright 1998, S.D. Personick. All Rights Reserved12 Capturing Analog Images Use a camera or scanner (transducer) to produce a signal or a set of data which represents the image Communicate this signal or data to a receiving location Use the received signal or data, which is not necessarily identical to the transmitted signal or data, to reconstruct a new image

13. Copyright 1998, S.D. Personick. All Rights Reserved13 Representing Images

14. Copyright 1998, S.D. Personick. All Rights Reserved14 Representing Images Character-mapped Images -The image consists of a number of “characters” or objects selected from a data base -To capture the image, one must obtain or derive its description in the form of: data that represents each character or object used; data representing its location on the image; data describing colors used, fonts, object sizes, object and character overlaps, etc. -The set of data is communicated to the receiving location and used to recreate the image

15. Copyright 1998, S.D. Personick. All Rights Reserved15 Character Mapped Images Figure 1

16. Copyright 1998, S.D. Personick. All Rights Reserved16 Representing Images Scanned images -Scan the image …e.g., left-to-right, and top-to- bottom -Represent the scanned brightness and color (e.g., red, green, and blue color brightness) by a set of signals which change in time as the scanning point moves -Communicate these signals to the receiving location; and use them to “paint” a new image with a complementary scanning process

17. Copyright 1998, S.D. Personick. All Rights Reserved17 Scanned Images Scan

18. Copyright 1998, S.D. Personick. All Rights Reserved18 Representing Images Bit-mapped Images -Divide the image into an n x m array of “pixels” (e.g., 800 x 600) -Represent the brightness and color of each pixel (e.g., red, green, and blue color intensities) by a set of numbers -Communicate these numbers to the receiving end, and use them to recreate the image

19. Copyright 1998, S.D. Personick. All Rights Reserved19 Bit-mapped Images

20. Copyright 1998, S.D. Personick. All Rights Reserved20 Bit Mapped Image Example An image contains 800 x 600 = 480,000 pixels 3 bytes of information are required to represent the intensity and color of each pixel To store this image you would require 480,000 x 3 bytes of memory To transmit this image in 1 second, you must transmit at a data rate of 480,000 (pixels) x 3 (bytes per pixel) x 8 (bits per byte) bits per second

21. Copyright 1998, S.D. Personick. All Rights Reserved21 Representing Images Transforms -Example: Hadamard transform (for a single color) What is the average brightness across the entire image? What is the difference in the brightness of the upper left quadrant vs the upper right quadrant? Upper left vs lower left? Upper right vs lower right? Etc., …

22. Copyright 1998, S.D. Personick. All Rights Reserved22 Transform Image Representation

23. Copyright 1998, S.D. Personick. All Rights Reserved23 Transforms Creative use of transform coding can reduce the amount of information required to represent an image. Example -if the intensity and color of an image isn’t changing across a selected portion of the image, then a single set of intensity and color data (e.g., 3-12 bytes) plus some location information can represent that entire portion of the image

24. Copyright 1998, S.D. Personick. All Rights Reserved24 Video

25. Copyright 1998, S.D. Personick. All Rights Reserved25 Video (continued) A video is a sequence of images (called “frames”), typically presented to a viewer at 24-80 frames per second If the images within the video are captured by scanning, then each image may be scanned twice, with “interlaced” scans. Thus each image may be represented by two interlaced “fields”. (e.g., NTSC video uses 60 interlaced fields per second = 30 frames per second).

26. Copyright 1998, S.D. Personick. All Rights Reserved26 Interlacing Field #1 Field #2

27. Copyright 1998, S.D. Personick. All Rights Reserved27 Video (continued) Given a fixed number of scan lines per second, the use of interlacing allows one to increase the field rate-- to reduce the perceptual artifact called “flicker”-- while maintaining a high enough number of scan lines per frame. For some applications (e.g., computer displays of multimedia information) the use of “progressive scanning” (no interlacing) is preferred. Experts disagree of the relative merits of progressive scanning vs interlaced scanning

28. Copyright 1998, S.D. Personick. All Rights Reserved28 Video (continued) While a traditional video signal is generated by a video camera that scans the (moving) images formed on its focal plane, many modern “videos” may be created using computer generated video (i.e., animations, like the original Walt Disney animations), where each image in the video sequence is intrinsically a bit mapped image or some standard compressed image file

29. Copyright 1998, S.D. Personick. All Rights Reserved29 NTSC Video Scan rate = 15,750 “lines” per second Frame rate = 30 frames per second Field rate = 60 fields per second Scan lines per frame = 525 (262.5 x 2, interlaced) Bandwidth of scanned signal (B&W information) = 6 MHz

30. Copyright 1998, S.D. Personick. All Rights Reserved30 Video Compression Coding Remove redundant information within each frame, as in image compression coding Remove redundancy that exists from frame-to- frame by -communicating only the differences that exist from one frame (or several prior frames) to the next -employing motion prediction/compensation for moving objects