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.
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.
At the end of the course, students will be able to: 1) understand the signal and image processing terminology (2) describe and apply the main tools of signal and image processing (3) analyse the obtained results in a critical way.
Linear algebra, basic calculus, programming
Class (44 hours) and guided labs (12 hours)
Students will learn basic tools for analyzing one- and two-dimensional signals in space, time and frequency. Main topics of the course: Fourier series, Fourier transform, Linear systems, Kalman filter, Wavelet. Applications of filtering in space and frequencies to digital images.
Notes, readings, slides shared by the instructors on Aulaweb. Books: Orfanidis "Introduction to Signal Processing"; Oppenheim et al. "Discrete-Time Signal Processing"; Gonzales Woods - "Digital Image Processing"
Ricevimento: Appointment by email: francesca.odone@unige.it (always specify name and surname, course name, degree name)
Ricevimento: Appointment by email
ALESSANDRO VERRI (President)
ANNALISA BARLA
FRANCESCA ODONE (President Substitute)
In agreement with the calendar approved by the Degree Program Board of Computer Science.
Written test to assess the entry level requirements. Oral exam on the entire program with a discussion of the assignments
The knowledge acquired and the achievement of a sufficient degree of mastery of the mathematical and computational tools at the basis of the teaching will be evaluated through a short written test. The acquisition of skills on the fundamentals of signal and image processing will be verified through homework and oral exam.
