1. Assessment classifications

2. Effort allocation sheet

You are required to work on the coursework in a group of members. Each group will submit an effort allocation sheet along with the report and workable code. The effort allocation sheet is shown below.

Group: x (x = 1, 2, ……, N)

The ideal situation to the contribution (in %) is that all members in the group make full efforts towards the completion of the coursework (fully learned from the coursework exercise), and are allocated 100% as contribution. Otherwise the true contribution is expected, such 80%, 50%, 20%, etc.

3. Assignment description

This group coursework assignment aims to enhance your understanding of image compression. Specifically, the challenge is for the group to devise and implement ways to reduce the size of natural images to occupy the least amount of storage while preserving quality. All images used in this assignment can be downloaded from the Blackboard site under: Image Analysis (Merged 2022/23) > Assessment > Images for assignment 2.

The group should choose the compression technique(s) and programming language. The group is encouraged to develop as much original code as possible (marks will be awarded for effort); if the group chooses to use code from elsewhere it must be fully acknowledged – the group must not totally rely on other sources.

The group needs to develop two pieces of code: for compression & decompression. Results should show the original image, compression ratio achieved by the compression, and the compressed-then-decompressed image.

Specifically, the basic requirement is to demonstrate: compression/decompression cycle:

• load and display original image

• compress image and save to memory

• read compressed image from memory

• decompress and display image

• compute and display compression ratio (CR) statistic.

Additional marks will be awarded if the compressed image can be written to/read from disk, and any other features implemented (e.g. additional metrics such as MSE; different compression levels; implemented user interface) – see mark breakdown.

4. Assignment submission requirements

A formal report in PDF is required (including preamble and appendices, as appropriate). It is expected that the following sections/items are included in the report.

− Abstract

− Introduction

− Methodology (theory; implementation details, e.g. language and libraries used, data structures, functions)

− Results (what has been achieved, with representative results (example images) and discussion)

− Conclusion and possible future work, references, acknowledgements

− Appendix(ces)

The original code (with detailed comments) should be attached at the end of the report as an appendix. You may implement your algorithms in any programming language, e.g. C/C++, Matlab, Java, Python, etc. Matlab/OpenCV functions may be used in the implementation with relevant techniques explained clearly.

A demonstration session will also be organized in Week 11. In this session you are expected (as a group) to provide a walkthrough of your developed compression solution. A detailed marksheet for the demonstration is on Blackboard. Further details on the demonstration schedule will be announced in class and made available on Blackboard nearer the time.

Additional information

To produce the formal report, you may refer to the “CS Style Guide for reports”, which is placed on the Blackboard under the item of “Teaching materials.