Colorimetry and Color Management for Cultural Heritage
A.Y. 2024/2025
Learning objectives
The student will be able to face colorimetry from many points of view: technical, physical and perceptual, regarding measures, management and reproducton of color.
These aspects will be studied in the context of cultural heritage.
These aspects will be studied in the context of cultural heritage.
Expected learning outcomes
Understanding, management and problem solving of colorimetry and lighting problems, applied to cultural Heritage.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
Human vision system (HVS)
Radiometry and photometry
Lighting for cultural heritage
CIE standard observer
Color matching functions
CIE colorimetry
Perceptual color spaces and atlases
Color differences
Gamut mapping
Dynamic range of luminance and HDR images
Computational models of HVS
Radiometry and photometry
Lighting for cultural heritage
CIE standard observer
Color matching functions
CIE colorimetry
Perceptual color spaces and atlases
Color differences
Gamut mapping
Dynamic range of luminance and HDR images
Computational models of HVS
Prerequisites for admission
none
Teaching methods
Class lessons and exercises
Teaching Resources
Course slides
"Misurare il colore", a cura di Claudio Oleari, Ed. Hoepli, seconda edizione (2008)
J.J. McCann, A. Rizzi, "The Art and Science of HDR Imaging", John Wiley, ISBN: 978-0-470-66622-7, pp. XXV+389, (2011).
"Misurare il colore", a cura di Claudio Oleari, Ed. Hoepli, seconda edizione (2008)
J.J. McCann, A. Rizzi, "The Art and Science of HDR Imaging", John Wiley, ISBN: 978-0-470-66622-7, pp. XXV+389, (2011).
Assessment methods and Criteria
The final exam is a colloquium. It aims at verify the level of competences acquired and the student capability in facing autonomously problems related to the course topics.
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 6
Lessons: 48 hours
Professor:
Rizzi Alessandro
Professor(s)