Introduction

1. Introduction • What are we going to learn? • Course outline. • Some details. • Assessment. • Introduction to media technology and revision.

2. Course outline • Introduction and revision. • Text and e-mail. • Audio. • MIDI. • Video. • Graphics. • Image manipulation. • Compression techniques. • Video compression 1 • Video compression 2 • Audio compression. • Revision. • Time constrained assignment.

3. Who, Where and When? • Who am I ? – Dr. Malcolm Wilson. • Where am I ? – Rm. MR15, but not all the time. • Email ? - malcolm.wilson@northampton.ac.uk • Course notes – eng.nene.ac.uk/~malc.

4. Who, Where and When? • New topic every week. • Assignment 1 – Issued week 9-10, hand in week 18 (After Easter). • Assignment 2 – Time constrained assignment in the final class.

5. Media Technology • Primarily concerned with the following digital media: • Text • Graphics • Animation • Synthesised Sound (Headphones) • Digitised Sound (Headphones) • Digitised Images • Digitised Moving images. • Multimedia is the integration of the above. • This is NOT a multimedia course.

6. Media Technology • Some of the above are computer generated. • Others are digitised representation of real-world data. • The computer data which represents these categories may be also subdivided into: • Static (images) • Continuous (sound, movies)

7. Media Technology

8. Data Files • All of the media data have specific file types. • The extension identifies the file type. • Examples: • Mydrawing.gif, “.gif” identifies a graphics file. “gif” stands for “graphics interchange format” • Mynoise.wav, “.wav” identifies a sound. “wav” is short for (sound) wave.

9. Data Files • Most media data files contain and start with “headers”. • “Headers” contain information about the file such as: • How long it is. • How it should be played back. • How it is coded. • Media files are often specially coded forms of the original data.

10. Text • Plain text and formatted text. • Plain text is usually coded in “ASCII” (American Standard Code for Information Interchange). • A 7 bit code which allows 128 characters. • Computers usually deal with 8 bits so ASCII appears to “waste” one bit.

11. Text • “ASCII” coded text was originally designed to connect terminals (keyboard and text monitors) to remote computers. • Errors could occur in the connection. • Bit 8 used for parity checks.

12. ASCII • Full list of ASCII codes will appear on my website and will be given as a handout. • But common letters and numbers are easy to remember. • Upper case letters • Add 64 (decimal) (40 (hex)) to position in alphabet. • Eg Code for B is 64 + 2 = 66 • Or 40 + 2 = 42 in hexadecimal.

13. ASCII • Lower case letters • Add 96 (decimal) (60 (hex)) to position in alphabet. • Eg Code for a is 96 + 1 = 97 • Or 60 + 1 = 61 in hexadecimal. • Numbers • Add 48 (decimal) (30 (hex)) to number. • Eg Code for 5 is 48 + 5 = 53 • Or 30 + 5 = 35 in hexadecimal. • Working in hex may be easier.

14. Parity • Since we mentioned it. • Error checking mechanism. • Odd or even, (but we decide first). • In 7 bit code (like ASCII) we use the 8th (MSB) for parity. • We set the bit to one or zero to make the total number of 1’s odd (for odd parity) or even (for even parity).

15. Odd Parity • Example 1 • Say our seven bit number is 011101. There are 4 ones. • We add an 8th bit of value 1 to make the total number of ones odd, giving (1)011101. • Example 2 • Say our seven bit number is 010101. There are 3 ones. • We add an 8th bit of value 0 to keep the total number of ones odd, giving (0)010101.

16. Even Parity • Example 1 • Say our seven bit number is 001101. There are 3 ones. • We add an 8th bit of value 1 to make the total number of ones even, giving (1)001101. • Example 2 • Say our seven bit number is 110101. There are 4 ones. • We add an 8th bit of value 0 to keep the total number of ones even, giving (0)110101.

17. Parity • Checked by receiving computer to see if there is an error. • Can you see a problem with this? • Clue - 2 errors. • Midi code (for sound synthesiser communication) very similar to ASCII, but no parity.

18. Graphics - Vector Images • Image composed and stored as a sequence of preset shapes or objects. • Lines, rectangles, ellipses, text etc. • Described in terms of size, position, drawing colour, fill colour. • Each object’s characteristics can be edited independently while in this graphical form.

19. Graphics – Vector Images • Differs from a bitmap image which we will see later. • Often called vector graphics. • Common drawing packages allow the creation of this form of image. • Once converted into bitmap or (raster form) we can no longer edit individual shapes.

20. Graphics – Vector Images • Example of a graphic vector image created using “Autoshapes”. My text in red • Other popular vector graphic tools are Paint shop pro and Photoshop.

21. Bitmaps - Raster Images • Does not use individual shapes. • Whole image contains many pixel elements (pixels). • Pixels are generally defined by colour alone.

22. Bitmaps - Raster Images • We cannot edit or change any shape drawn without changing all of the pixels concerned. • Microsoft Paint produces Bitmap images. • Once a vector graphic image has been converted to a bitmap it cannot be converted back.

23. Bitmaps - Raster Images • If we “paste” from a vector graphics image into Paint the pasting process converts the vector graphic to a bitmap. • We can no longer edit the pasted image. • Try it. • Digitisation of real-life images produces bitmap images.

24. Moving images and animations • Images may be given the illusion of motion. • We display a succession of changing “frames” to give this illusion. • Moving raster images are usually called “movies” in computer media jargon. • Moving graphics (vector images) are called animations.

25. Sound • Just like images we can have two forms in the computer. • One form remembers the pitch, duration and loudness and individual sound of the notes. • This is stored as MIDI (musical instrument digital interface) form. • Like vector graphics the sound can be edited by changing the individual characteristics of the notes.

26. Sound • Other form relies on digitisation of real life sounds. • Sampled sound. • A common example of this are “wav” sound wave sounds. • Like bitmap images we cannot edit individual notes without changing all of the samples which the note is comprised of.

27. Digitisation • Real-life images and sounds need to be digitised for computer representation. • Turning an analogue or continuous signal into a digital signal. • There are 3 stages to digitisation. • Sampling • Quantisation. • Coding.

28. Sample rates and Bandwidth. • The bandwidth of audio and video signals can be considered to be the highest frequency carried by the signal. • In sound “crispness”. • In vision “sharpness”.

29. Sample rates and Bandwidth. • Sample rates must be (at least) twice the bandwidth • High quality audio requires a bandwidth of 20 KHz. • A sample rate of 44.1 kHz or 48 kHz is chosen.

30. Data rates and file sizes. • So an 16 bit audio signal sampled at 44.1 kHz produces 16 x 44100 = 705600 bits per second. • Double this for stereo • 1411200 or 1.4112 Mbps. • High quality video uses a 270Mbps data stream to allow for a 10bit 625 line television picture.

31. Data rates and file sizes. • CD ROM holds about 700 MBytes. • How much audio? • How much video?

32. Data rates and file sizes. • DVD holds about 15 GByte max. • How much audio? • How much video?

33. Data rates and file sizes. • Original CD ROM could only deliver data at 1.2 Mbps. • 40 x is therefore 48 Mbps. • DVD data rate (single speed) 11 Mbps. • 16 x now exist giving 176 Mbps. • Still can’t do telly?

34. Compression • Digitised sound and video produces a lot of data. • In particular digitised television quality pictures produce data at 270 Mbits/second which is faster than most hard disks, CD roms and networks devices can accommodate. • We need to compress data for use on computers.

35. Compression • We have two types of compression. • Lossy compression and lossless compression. • As the names suggest lossy compression loses some of the original signal, while lossless does not. • Lossless techniques such as run-length encoding and Huffman coding achieve compression by creating shorter codes. This is not always possible.

36. Compression • Lossy techniques rely on throwing away some information which the viewer or listener will not notice too much. • Involves changing the data to some other form. (Transform) • Most lossy techniques are noticeable. • The more lossy compression that is applied, the more the compression effect will be noticeable.