Image Processing
Subject code: SIP 7007

---

Lecturer:
Dr Jimmy Li
Flinders University of South Australia

Mode of delivery
On-line with possibility of weekly lectures.

Assumed knowledge
Linear algebra (matrices), a basic knowledge on differential equations (linear systems) and probability theory, MATLAB.

Aims/Learning Objectives
To provide the student with knowledge of the theories and applications of selected topics in image processing including but not limited to median based detail-preserving filters, image interpolation using MAP and other methods, frequency and spatial domain based approaches for super-resolution image reconstruction, motion estimation, optical flow, edge detection and various image enhancement techniques.

To familiarize the student with some important concepts and analytical techniques for linear and non-linear image processing.

To give the student experience in image processing applications and research using MATLAB.

To familiarize the student with a board range of tools and techniques for image filtering and enhancement, image expansion, reconstruction of super-resolution images, motion estimation, and etc.

Content
Image enhancement: Histogram modification (quantization): image space, Fourier smoothing; Sharpening: highpass filters, differential operators; Model based; Masking.
Image segmentation: thresholding: global, local; Feature detection and representation: point detection, edge detection, boundary detection, line detection; Region growing; Texture analysis; Classification.
Compression: Model based; Quantization, Filter based.
Image registration: many techniques listed above; Geometric transformations.

Assessment
Details of the actual assessment used in a given year can be found in the study guide provided at the start of the semester.

Resources
All the materials necessary for the course will be availabe on-line. The lecture notes also include an extended bibliography for further reading on the subject.