OVERVIEW

The course is aimed at:

Students who intend to enroll in the MSc in Computer Science, with the aim of providing a "warm up" for the courses of the Artificial Intelligence track.
Students who do not intend to continue their studies, with the aim of introducing the basic information for the processing of signals and images through the application of the Discrete Fourier Transformation.

AIMS AND CONTENT

LEARNING OUTCOMES

Learning the basic tools for signal and image processing. Delving into some classic processing problems. Learning how to structure, implement, and validate methods that address a signal processing problem on real data.

AIMS AND LEARNING OUTCOMES

By the end of the course, the student will have acquired the tools to process signals and images in their original domains (time or space) as well as in the frequency domain.

Specifically, the student will be able to:

• Enhance signals and images by increasing the signal-to-noise ratio or reducing noise
• Highlight interesting features in signals or images.

PREREQUISITES

The course assumes prior knowledge of calculus, linear algebra, and a solid foundation in programming.

TEACHING METHODS

The course includes:

• theoretical lessons supplemented with in-depth study material for independent study
• An individual project activity conducted in class, under the supervision of the instructor

SYLLABUS/CONTENT

• Signals 1D and 2D and Sampling
• Introduction to Discrete Fourier Transform
• Discrete Convolution
• Linear Filters on 1D and 2D Signals (Noise Reduction and Feature Enhancement)
• 1D Applications: Sound and Time Series
• 2D Applications: Color Image Processing, Pixel Operations, Geometric Operations

RECOMMENDED READING/BIBLIOGRAPHY

Handouts, links, and slides will be provided by the instructor.

TEACHERS AND EXAM BOARD

Exam Board

FRANCESCA ODONE (President)

MATTEO MORO

NICOLETTA NOCETI (President Substitute)

LESSONS

LESSONS START

According to the calendar approved by the Degree Program Board: https://corsi.unige.it/en/corsi/8759/studenti-orario 

Class schedule

The timetable for this course is available here: EasyAcademy

EXAMS

EXAM DESCRIPTION

The assessment consists of two parts:

• Evaluation of the project activity, which includes a brief presentation of the work done  
• Written exam on the covered program

Guidelines for students with certified Specific Learning Disorders, disabilities, or other special educational needs are available at  https://corsi.unige.it/en/corsi/8759/studenti-disabilita-dsa

ASSESSMENT METHODS

The student will need to demonstrate, through the development of software and the analysis of results conducted independently, an understanding of the theoretical and practical aspects of signal or image analysis.

Additionally, the writing of the project report and the presentation will aim to evaluate the student's expression and summarization skills.

FURTHER INFORMATION

For further information, please refer to the course’s AulaWeb module or contact the instructor.