The course aims at providing the students with the basic tools that are required for image analysis and modeling with focus on bioinformatics. This will consist of the generalization of the main signal analysis methods to the 2D case, enriched with 2D specific tools. Among the main topics are the Fourier and Wavelet transforms, the multi-scale representation and analysis, color imaging, as well as techniques for image segmentation and classification.
Among the main topics are
- Image acquisition
- Sampling in 2D
- Quantization noise
- 2D Fourier transform (space-frequency analysis)
- 2D Wavelet transform (multiscale representation)
- Edge detection
- Filtering (denoising, deblurring, image enhancement)
- Basics of mathematical morphology
- Image segmentation and performance assessment
- Color imaging
- Foundations of pattern recognition (classification, clustering)
- Applications to microarrays and biomedical images
Oral and miniproject. However, the oral could be replaced by a written exam with the same structure.
L0-Introduction
(pdf, it, 5481 KB, 03/02/09)
L10-Wavelets
(pdf, it, 576 KB, 19/03/09)
L1-Basics
(pdf, it, 1914 KB, 03/02/09)
L2-2DFourierTransform
(pdf, it, 2663 KB, 03/02/09)
L3-2D-DFT
(pdf, it, 206 KB, 05/02/09)
L4 - 2D Linear Systems
(pdf, it, 8028 KB, 19/02/09)
L5 - Edge Detection
(pdf, it, 3644 KB, 19/02/09)
L6-Stat-sig-proc
(pdf, it, 838 KB, 05/03/09)
L7-ColorImaging
(pdf, it, 3204 KB, 05/03/09)
L8-Segmentation
(pdf, it, 1376 KB, 19/03/09)
L9-Microarrays
(pdf, it, 4619 KB, 19/03/09)
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