1. To understand the nature of images as information regarding colors and luminance.
2. To extend the mathematical tools used in 1D signal processing to the two dimensions.
3. To understand the problems that are handled by Digital Image Processing (Scene analysis, noise reduction, detection/recognition of objects, etc.)
4. To understand the theoretical aspects of tools (mathematical/algorithmic) used for the solution of the above problems.
5. To gain practical experience in the development of Digital Image Processing algorithms via simulation of selected image processing tools in Matlab.
Course Content (Syllabus)
1. Image perception and acquisition – Luminosity and Colors.
2. Digitization (Sampling and Quantization)
3. Images as 2D signals
3.1 Fourier and z image transforms
3.2 Convolution, Convolution theorems
3.4 2D stochastic processes
4. Image analysis
4.1 Edge and salient point detection
4.2 Image segmentation
4.3 Image feature extraction
4.4 Shape and contour computation
5. Image Enhancement
5.1 Color enhancement
5.2 Noise reduction
5.3 inverse filtering, Wiener filter
6. Multirate analysis/synthesis