1. Introduction to Image Processing Grass Sky Tree ? ? Review

2. Exam Paper Format Duration: One Hour Format: Answer 3 out of 4 Questions

3. Question 1 Digital Image Fundamentals –image sensing & acquisition; sampling & quantisation; spatial resolution & aliasing; image representations; colour models: additive vs. subtractive; alternative colour spaces: RGB, HSV, CMYK, YUV Point Processing –intensity transformation: contrast reversal (negatives), log, power-law; contrast stretching using piecewise linear transform functions; bit-plane slicing; histogram equalisation & matching; arithmetic/logic operations

4. Question 2 Neighbourhood Processing (Image Filtering) –noise models: uniform, Gaussian, impulse & periodic; convolution vs. correlation; linear filters: mean (box), weighted average & Gaussian; nonlinear filters: minimum, maximum & median; bilateral filtering; handling of edge pixels; separable filters; edge detectors: 1 st and 2 nd derivatives gradient operators; Roberts, Prewitt, Sobel, Laplacian operators & their mathematical formulations

5. Question 3 Image Segmentation –purpose and main approaches of segmentation; over & under-segmentation; thresholding: global, local, adaptive and multi-level; algorithms: iterative global thresholding & Otsu, connected components & 2- pass labelling –texture, region growing, split & merge and motion segmentation; background extraction; edge linking, i.e. local vs. global processing using Hough transform (no mathematical details required) –4 vs. 8-neighbours; object representation & description, e.g. normalised chain codes & shape number

6. Question 4 Spectral Techniques –Fourier theory and discrete Fourier transform; magnitude and phase of image spectra; filtering in the frequency domain and its advantages; convolution theorem; basic filtering steps in the frequency domain; differences between low, high & bandpass filters; ideal vs. practical spectral filters, e.g. Butterworth filters; image enhancement vs. image restoration; inverse filters