OVERVIEW

Language: Italian

This course consists of 26 hours of lectures. Moreover, 22 laboratory hours have been planned

AIMS AND CONTENT

LEARNING OUTCOMES

The course objective is to provide specialized mathematical training on the proper methods of reconstruction and image processing with particular reference to the processing of astronomical images.

TEACHING METHODS

Teaching style: In presence

SYLLABUS/CONTENT

Basics of image processing: 1)  Image formation and image recording: blurring and noise. 2) Digital images: sampling and quantization. Basic relationships between pixels. 3) Two dimensional Discrete Fourier Transform, two dimensional Fast Fourier Transform algorithm (FFT 2D) and Fourier Transform of an image. 4) Basic operators for image processing. Edge detection. Hough Transform for feature extraction.

Astronomical image processing: Image reconstruction from visibilities: definition of visibility; inverse Fourier Transform from limited data; interpolation in Fourier space; deconvolution techniques; iterative methods for image reconstruction. The NASA RHESSI satellite.

RECOMMENDED READING/BIBLIOGRAPHY

1. Bertero M and Boccacci P 1998 An Introduction to Linear Inverse Problems in Imaging (IOP, Bristol)
2. R.C. Gonzalez and R.E. Woods. Digital Image Processing 2nd edition. Prentice-Hall. 2002

TEACHERS AND EXAM BOARD

Exam Board

Anna Maria MASSONE (President)

FEDERICO BENVENUTO

MICHELE PIANA

LESSONS

LESSONS START

The class will start according to the academic calendar.

Class schedule

IMAGE PROCESSING

EXAMS

EXAM DESCRIPTION

Oral.

Exam schedule