The course presents the theoretical foundations and fundamental applications of signal processing and image analysis. It places special emphasis on topics that will develop the innovative spirit and creative focus needed to meet the challenges of the future.
The course aims to expose the bases of the theory of the signal, in particular the mathematical description of the signals. This formal description makes it possible to highlight the various characteristics and properties of signals. The advanced theoretical elements make it possible to develop the principal tools of signal processing, tools which will be used in many technical and scientific fields.
The following subjects will be studied: Signal acquisition, analog signal, analog-digital conversion, digital signals and systems, discrete Fourier transform, fast transform algorithm (FFT), correlation, convolution, RIF and RII filter synthesis, digital filtering, image processing (coding, histogram, unit transforms, filtering, enhancement and restoration, mathematical morphology, edge detection and segmentation, multi-resolution,..), the wavelet transform, an introduction to artificial intelligence and artificial neural networks.
An oral exam will assess the students' ability to understand and use the tools developed for signal and image processing.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Master in Physics, Professional focus in Physics and Data | Standard | 0 | 4 | |
| Master in Physics, Teaching focus | Standard | 0 | 4 | |
| Master in Physics, Research focus | Standard | 0 | 4 | |
| Master in Physics, Professional focus | Standard | 0 | 4 | |
| Master in Physics, Teaching focus | Standard | 1 | 4 | |
| Master in Physics, Research focus | Standard | 1 | 4 | |
| Master in Physics, Professional focus | Standard | 1 | 4 | |
| Master in Physics, Professional focus in Physics and Data | Standard | 1 | 4 |