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Course Syllabus Form
1 University of Bahrain – Quality Assurance& Accreditation Center ‐ Course Specification
1. College: College of Applied Studies 2. Department: Technical Programs 3. Program: Associate Diploma in Multimedia Applications 4. Course code: CSA 215 5. Course title: Data Compression Techniques 6. Course credits: 2‐3‐3 7. Pre‐requisites: CSA 116 8. Course web‐page: BaseL.co.nr 9. Course Instructor/coordinator: Mr. Basel Bani‐Ismail E‐mail: [email protected] , Office Telephone:1743‐5063 Office Room: 20C‐132, Office Hours: U:11‐12,1‐2; M:10‐11; T:11‐1; W:1‐2; H:1‐2 10. Academic year: 2009/2010 11. Semester: First X Second Summer 12. Textbook(s):
• B1: Mark Nelson and Jean‐loup Gailly, The Data Compression Book, Second Edition, M&T Books, New York, NY 1995.
• B2: Ze‐Nian Li and Mark S. Drew, Fundamentals of Multimedia, Prentice‐Hall, 2004. 13. References:
14. Other resources used (e.g. e‐Learning, field visits, periodicals, software, etc.):
• WinZip Version 10.0 or above. • WinZip Command Line Support Add‐On Version 2.0 or above. • Lab Manual.
15. Course description (from the catalog): The primary purpose of the course is to explain various data‐compression techniques used on personal and mid‐sized computers. It covers lossless and lossy algorithms, the modeling‐coding paradigm and statistical and dictionary schemes and contains source code for algorithms in C, It explains very well the ideas and basics of data compression algorithms and gives a good categorizing of the compression area. Also the course explores different data compression methods, explaining the theory behind each and showing C programmers how to apply them to significantly increase the storage capacity of their system.
16. Course Intended Learning Outcomes (CILOs): Mapping to PILOs
CILOs a b c d e f g 1. Define compression; understand compression as
an example of representation. X
2. Understand the idea of lossy and lossless compression.
X
3. Describe elementary techniques for modeling data and the issues relating to modeling.
X
4. Understand the most common file formats for image, sound and video.
X X X
5. Distinguish the basic techniques of lossless compression.
X
2 University of Bahrain – Quality Assurance& Accreditation Center ‐ Course Specification
17. Course assessment: Assessment Type Number Weight
Quizzes 3 5 % Midterms 2 40 % Lab Exam 1 10 %
Lab Assignments 3 5 % Final 1 40 % Total 10 100 %
18. Course Weekly Breakdown:
Week Date Topics covered PILOs Teaching Method
Assessment
1 21/2‐25/2 B1‐Ch.1: Introduction to Data Compression. a Lecture
2 28/2 ‐ 4/3 Prophet’s Birthday Holiday B1‐Ch.2: The Data‐Compression Lexicon, with a History.
a Lecture
3 7‐11/3 B1‐Ch.2: The Data‐Compression Lexicon, with a History. a Lecture, Lab
4 14‐18/3 B1‐Ch.2: The Data‐Compression Lexicon, with a History. a Lecture, Lab
5 21‐25/3 Handout: Image, video and sound file formats. a, b, g Lecture, Lab
Lab Assignment 1
6 28/3 ‐ 1/4 B2‐Ch.7: Shannon‐Fano Algorithm. a Lecture, Lab Quiz 1
7 4‐8/4 B2‐Ch.7: Shannon‐Fano Algorithm. a Lecture, Lab
8 11‐15/4 B2‐Ch.7: Huffman Coding Algorithm.
a Lecture, Lab Lab Assignment
2
9 18‐22/4 Mid‐semester break
10 25‐29/4 B2‐Ch.7: Adaptive Huffman Coding.
a Lecture, Lab Quiz 2
11 2‐6/5 Labor Day Holiday B2‐Ch.7: Adaptive Huffman Coding.
a Lecture
12 9‐13/5 B2‐Ch.7: Arithmetic Coding (Encoding)
a Lecture, Lab Midterm 1 11/5/2010, Time: 11‐12
13 16‐20/5 B2‐Ch.7: Arithmetic Coding (Decoding) a Lecture, Lab
Lab Assignment 3
14 23‐27/5 B2‐Ch.7: LZW (Compression) a Lecture, Lab Quiz 3
15 30/5‐3/6 B2‐Ch.7: LZW (Decompression) a Lecture Lab Exam 30/5/2010, Time: 2‐3
16 6‐10/6 Revision a Lecture Midterm 2
8/6/2010, Time: 3‐4
17 17‐06‐2010
Final Exam, Time: 8:30‐10:30
