Multimedia Data Revision Dr Sandra I. Woolley Electronic, Electrical and Computer Engineering

Syllabus Summary I Data compression – Advantages and disadvantages – Lossless and lossy compression – Lossless compression » Huffman, Lempel-Ziv (eg.GIF) – Lossy compression » DCT (.JPEG) » Methods of quality assessment (objective vs. subjective methods) » Rate/distortion graphs Image data – Image filtering (simple high and low pass, edge and median filtering) – Photography, vision, colour and colour models

3 Syllabus Summary II Video data – MPEG-1 coding (what it is and how it works) Speech and audio – Sampling and quantization – Coding methods (waveform and vocoding) – Audio data (MP3 - perceptual audio coding) Web page authoring – HTML – Hypertext markup language – Animated gifs – JavaScript for dynamic web pages – SVG (Scalable Vector Graphics)

Supporting Resources

Revision Suggestions  Read/work through the slides and examples.  Include laboratory exercise material in your revision.  Work through at least one past exam paper.  See on-line revision materials and use the University exam paper database For this subject a keyword search on multimedia should pull up all the papers. When using this database always be very careful that you are reading the right examination paper. Because the syllabus is regularly updated, I suggest using papers from only the last two years for this subject.  Time your attempts on at least two questions.  Work out your exam technique in advance. –e.g., Allocate a set amount of time to read through all questions carefully and write down the order to attempt them (even if others already need more paper).

Exam Pointers  2 of 3 questions to be answered.  Take a calculator.  Read questions carefully.  Keep a close eye on the time.  Keep descriptive answers short and to the point.  Use diagrams, tables or bullet-point lists if useful.

Common Mistakes  … that lose few marks  Small numerical slips. For example, getting some of array values wrong after filtering operations. Generally, loses no marks.  Misspelling loses no marks (unless it results in ambiguity). –Loosy and loosey are not words. “Loose” means too big. –Lossy and loss and lose are correct spellings.  Other numerical or algorithmic slips. For example, missing a character out of an LZ decompression. Loses few if any marks (unless slip makes question trivial or produces a blatantly wrong answer - in this case a short student note indicating awareness can pull back a mark or two.)  … that can lose more marks  Misreading the question.  Mixing up important terms like subjective and objective.  Mixing up compression methods.

Thank you and good luck See the course web page for past exam questions and solutions and a link to the university exam paper database.