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Abstract
Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping in JAVA. Application to real-world examples in industrial vision and biomedical imaging.
Objective
By the end of the course, the student must be able to: - Exploit the multidimensional Fourier transform - Select appropriately Hilbert spaces and inner-products - Optimize 2-D sampling to avoid aliasing - Formalize convolution and optical systems - Design digital filters in 2-D - Analyze multidimensional linear shift-invariant systems - Apply image-analysis techniques - Construct image-processing software - Elaborate morphological filters
Content
Introduction. Image processing versus image analysis. Applications. System components. Characterization of continuous images. Image classes. 2D Fourier transform. Shift-invariant systems. Image acquisition. Sampling theory. Acquisition systems. Histogram and simple statistics. Linear and Max-Lloyd Quantization. Characterization of discrete images and linear filtering. z-transform. Convolution. Separability. FIR and IIR filters. Image-processing operations. Point operators (thresholding, histogram modification). Spatial operators (smoothing, enhancement, nonlinear filtering). Morphological operators. Introduction to image analysis and computer vision. Segmentation, edge detection, objet detection, image comparison.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Image Processing I (EPFL)
**Course at EPFL**
|
No time listed | 3 h weekly |
Offered In
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Nuclear Engineering Master (MSc Nuclear Engineering is a joint program of EPF Lausanne and ETH Zurich. The first semester takes place in Lausanne. Students therefore have to enroll at EPFL. For more information about the curriculum and courses see: ?)
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