DIGITAL SIGNAL & IMAGE PROCESSING

DIGITAL SIGNAL & IMAGE PROCESSING

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Code
90520
ACADEMIC YEAR
2019/2020
CREDITS
9 credits during the 1st year of 10852 COMPUTER SCIENCE (LM-18) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
INF/01
LANGUAGE
English
TEACHING LOCATION
GENOVA (COMPUTER SCIENCE )
semester
1° Semester
Teaching materials

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

Acquiring the basic tools for the analysis of signals in both the space and frequency domains, and learning the main image processing techniques for feature extraction, image segmentation, image registration, and image matching.

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

Ricevimento: Appointment by email

Ricevimento: Appointment by email

Exam Board

ANNALISA BARLA (President)

ALESSANDRO VERRI (President)

ISSA MOUAWAD

FRANCESCA ODONE

LESSONS

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

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

Date Time Location Type Notes
24/07/2020 09:00 GENOVA Esame su appuntamento
18/09/2020 09:00 GENOVA Esame su appuntamento
12/02/2021 09:00 GENOVA Esame su appuntamento