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Lab in signal and image processing

EE-490(f)

Lecturer(s) :

Vandergheynst Pierre

Language:

English

Withdrawal

It is not allowed to withdraw from this subject after the registration deadline.

Summary

These lab sessions will allow student to get familiar with time-frequency and time-scale tools to analyse complex signals. Algorithms to solve linear inverse problems will also be implemented and tested to restore degraded signals and images.

Content

• Introduction to main Matlab routines
• Gabor transform and frames
• Wavelet transform, frames and basis
• Implement a simple image coder
• Restore degraded audio signal
• Restore degraded images

Learning Prerequisites

Required courses

Digital signal processing or Signals and Systems

Recommended courses

Advanced Signal Processing

Learning Outcomes

By the end of the course, the student must be able to:

• Analyze a complex signal with a short-time Fourier transform
• Analyze a complex signal with a wavelet transform
• Design a software to compress a time series
• Design a software to restore a degraded signal
• Design a software to restore a degraded image
• Design a software to compress an image

Transversal skills

• Assess progress against the plan, and adapt the plan as appropriate.
• Write a scientific or technical report.