Multimedia information

A.Y. 2020/2021
Overall hours
Learning objectives
The course aims at studying how multimedia information is acquired, coded and processed by the most popular applications running on common multimedia systems. For this reason, the course will be focused on theoretical and practical elements particularly important for the manipulation of the three main multimedia modalities, i.e. images, videos and audios, which are the core of modern communication.
Expected learning outcomes
Students will learn the basic notions and tools about how information conveyed by images, videos and audios is handled and processed, which in turns means to be skilled at:
- capturing multimedia information through digital systems such as video cameras, TV or computers
- coding and representing multimedia data using fundamentals and techniques of information theory
- using algorithms and programming languages devoted to multimedia data processing
Course syllabus and organization

Single session

Lesson period
First semester
During the emergency phase, the course will be held online, if possible in synchronous way, using the Zoom platform. Lectures and practical classes will be recorded, stored on Ariel portal, and available for the entire semester.

the program and the material will not change with respect to the standard one.

The exam modality and the evaluation criteria will not change with respect to what indicated in the syllabus (ordinary modality).
The written exam will be held in presence or in a distance modality (according to the university guidelines) on the platform (for more details refer to the university portal)
Course syllabus
- Introduction to image acquisition, digitalization and processing
- light, color and the electromagnetic spectrum
- image formats and compression (JPEG)
- punctual transformations for image enhancement
- image filtering in spatial domain
- clusteting and image binarization
- key point detection and local descriptors
- optical flow
- introduction to the classification via convolutional neural networks
- examples and simulations with Python
- image quality augmenting filters
- video segmentation
- analog and digital video formats
- compression and video coding in the standard MPEG* and H.26*
- examples and simulations with Python
- Sound digitalization
- filters for sound analysis
- digital audio synthesis and effects
- MPEG* audio coding standard
- examples and simulations with Python
Prerequisites for admission
Fundamentals of digital signal processing
Teaching methods
The course consists of lectures and practical classes based on Python.
Teaching Resources
The lecture slides, the suggested books and Python exercises are available on the Ariel portal and on the course page
Assessment methods and Criteria
The examination consists of two parts:
1. a written test based on the lecture subjects (75% of final grade)
2. a practical test based on Matlab programming (25% of final grade)

Two partial exams are provided at mid- and end-course respectively.
Elementi di Elaborazione Audio e Video
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Grossi Giuliano
Elementi di Elaborazione Immagini
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
By email appointment
Room 4016, 4th Floor, via Celoria 18