OVERVIEW

The Digital Signal and Image Processing course aims at providing the basic tools for analyzing and processing 1D and 2D signals over time, space and frequency.

The course will consist in classes and guided labs.

The course has a strong applicative connotation. In addition to the labs, the student will work on a project that will require a great deal of autonomy to solve complex problems.

AIMS AND CONTENT

LEARNING OUTCOMES

Students will learn basic tools for analysing 1-D and 2-D signals in the space and in the frequency domains. Particular attention will be devoted to filters, to deal with noise attenuation and feature enhancement. Dynamic filters will also be considered. The course will also cover low level vision topics, including image feature extraction, image segmentation,image registration, and image matching. Students will be involved in project activities.

TEACHING METHODS

Class (44 hours), lab (12 hours), project (50 hrs) and outside preparation
Students are required to attend class and lab for a total of 6 hrs/week

SYLLABUS/CONTENT

Syllabus
Students will learn basic tools for analysing 1-D and 2-D signals in the
space and in the frequency domains. Particular attention will be devoted
to filters, to deal with noise attenuation and feature enhancement.
Dynamic filters will also be considered. The course will also cover low
level vision topics, including image feature extraction, image
segmentation,image registration, and image matching.
Students will be involved in project activities.
CONTENT:
Systems
- Systems: Input/Output signal, Response of a System
- Systems Properties: Linearity, Time-invariance, Causality
1D signals
- Complex numbers, Periodic Functions, Complex Functions,
Trigonometric Polynomial
- Fourier Series
- Fourier Transform
- Noise
- Sampling, Sampling Theorem
- Convolution Theorem
- Filters
- Kalman Filter
- Wavelets
2D signals
- Greyscale Images
- Color images
- Histogram
- 2d Fourier Transform
- Spatial filters
- Image features (corner, edge, ridge)
- Image matching
- Image similarity measures
 

RECOMMENDED READING/BIBLIOGRAPHY

Signals and Systems
Oppenheim et al. - Signals and Systems
Bertoni et al. - Introduzione all’elaborazione dei segnali (UniMi) (in Italian)

Digital Signal Processing
Orfanidis - Introduction to Signal Processing
Oppenheim et al. - Discrete-Time Signal Processing

Signal & Image processing
Gonzales Woods - Digital Image Processing
Mallat - A wavelet tour of signal processing

TEACHERS AND EXAM BOARD

Exam Board

ANNALISA BARLA (President)

PATRIZIA BOCCACCI (President)

VANESSA D'AMARIO

SAMUELE FIORINI

FRANCESCA ODONE

FEDERICO TOMASI

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The final evaluation will take into account: (1) class attendance, (2) planned homework, (3) project discussion (4) oral dissertation

ASSESSMENT METHODS

The project should be written clearly, complemented with working code and it should show that the student has fully understood the topic. Examples on different real scenarios are encouraged.

The oral examination consists in a discussion of the project and of the topics taught in class. 

Exam schedule