For each course unit, follow the terminology list as a guide to find out about and understand the algorithms identified. This material is intended as a guide and not as a complete set of notes, you should refer to the resources as a starting point for detailed material (this resource includes book and web references as well as some locally stored material).
You will need to attempt the practicals (Labs) associated with each unit in the order in which they appear as results from each project are used in subsequent assesed projects. Details of course assessment are provided for your information together with the dates for each submission of work.
The time allocation at the top of each unit and lab exercise should be used only as a guide. Use the mini questions (MCQ's) related to each unit and move on when you feel you can answer them reliably. Finally, "Terminology" are provided as examples of the level of understanding required to answer examination questions.
|Image Representation||Image Manipulation in MATLAB|
|Simple Image Processing||Histogram Modification|
|Frequency Domain and Convolution||Deconvolution|
|Image Noise/Corruption||Noise and Fourier Transforms|
|Types of Linear Filters||Filter Design|
|Rank Filters||Segmentation and Noise Filtering|
|Region Segmentation||Threshold-based Segmentation (Assessed)|
|Edge and Corner Detection||Edge Detection|
|Probability and Statistics||No practical|
|Pattern Recognition||Neural Networks|
|(c) Imaging Science and Biomedical Engineering 2000 [email@example.com]|