Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
ING-INF/05
12
B
ING-INF/05

2° Year   activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activitites
4
F
-
ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
ING-INF/05
12
B
ING-INF/05
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activitites
4
F
-
Modules Credits TAF SSD
Between the years: 1°- 2°
2 courses to be chosen among the following
6
C
INF/01
6
C
INF/01
6
C
INF/01
Between the years: 1°- 2°

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S003737

Coordinator

Gloria Menegaz

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

I sem. dal Oct 2, 2017 al Jan 31, 2018.

Learning outcomes

The course deals with the wavelet transform and its applications in image and signal processing. The WT can be considered as a generalization of the Fourier transform to the time/frequency (or time/scale) analysis domain. Accordingly, it allows to overcome some of the main limitations of the FT as the analysis of transient signals that can be characterized with precisely in both the time and the frequency spaces at the same time. Multiresolution analysis is particularly suitable for natural and biological signals, feature extraction for pattern recognition, denoising and image coding.

Laboratory
The course will be complemented by lab sessions aiming at acquiring the practical instruments that are needed in this framework as well as to solve some basic problems. This will be performed using the Matlab Wavelet toolbox. Classical paper-form exercises could also be performed.

Program

1) Fundamentals of signal and image processing
- Fourier transform in 1D and 2D
- Windowed FT

2) Wavelets and pyramids
- Introduction to the WT
- Wavelet basis
- Wavelet families
- Fast discrete wavelet transform (DWT)
- 2D discrete wavelet transform
- lifting-steps implementation
- Advanced concepts
- Applicatins

3) Advanced coding systems
- Wavelet-based coding
- JPEG2000

4) Wavelets in biomedicine

Examination Methods

The exam consists in an oral examination aiming at verifying the comprehension of the theoretical aspects and includes theorems and demonstrations. The evaluation of the lab. activity is through the analysis of the activities performed during the year.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Teaching materials e documents