PA172 Image Acquisition

Faculty of Informatics
Autumn 2023
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Mon 10:00–11:50 C511
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 50 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written online exam.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022.

PA172 Image Acquisition

Faculty of Informatics
Autumn 2022
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Tue 8:00–9:50 A320
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 50 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written online exam.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Autumn 2021
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Thu 16. 9. to Thu 9. 12. Thu 14:00–15:50 C511
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 49 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written online exam.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Autumn 2020
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught online.
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Mon 10:00–11:50 C511
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 49 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written online exam.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2019
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Tue 19. 2. to Tue 14. 5. Tue 8:00–9:50 B411
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 20 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2018
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Thu 8:00–9:50 C511
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 20 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
Student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the basic features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2017
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Thu 8:00–9:50 B410
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 20 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2016
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Thu 14:00–15:50 C511
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 20 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2015
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Thu 8:00–9:50 C525
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 19 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2014
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Fri 10:00–11:50 G126
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 19 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2013
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Fri 10:00–11:50 G125
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 19 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2012
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Wed 12:00–13:50 B411
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 19 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2011
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Mon 10:00–11:50 B411
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2010
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Fri 10:00–11:50 B410
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 21 fields of study the course is directly associated with, display
Course objectives
In this course the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attention is paid to the acquisition of multidimensional information. The student will gain basic understanding of both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2009
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Wed 8:00–9:50 C416
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
This course is aimed at theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attentiion is paid to the acquisition of multidimensional information. Both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory will be described.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Assessment methods
Lectures in Czech or English (in the presence of students who do not understand Czech), study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2008
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Wed 8:00–9:50 C416
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
This course is aimed at theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attentiion is paid to the acquisition of multidimensional information. Both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory will be described.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Assessment methods (in Czech)
Přednášky v češtině, studijní materiály v angličtině. Závěrečná zkouška v písemné podobě bez pomůcek.
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Spring 2007
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Wed 8:00–9:50 C416
Prerequisites
PV131 Digital Image Processing
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
This course is aimed at theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Special attentiion is paid to the acquisition of multidimensional information. Both hardware of specific detectors and transport of the information from these detectors to computer memory and representation in computer memory will be described.
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Assessment methods (in Czech)
Přednášky v češtině, studijní materiály v angličtině. Závěrečná zkouška v písemné podobě bez pomůcek.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA172 Image Acquisition

Faculty of Informatics
Autumn 2019

The course is not taught in Autumn 2019

Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Michal Kozubek, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics
Prerequisites
Knowledge at the level of the course PV131 Digital Image Processing is desirable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 49 fields of study the course is directly associated with, display
Course objectives
In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
Learning outcomes
The student will be able to:
formulate basic principles of digital image acquisition;
describe characteristics of the most common imaging instruments;
describe mutual interdependencies between the essential features of imaging instruments or settings;
suggest suitable configurations for a given image acquisition task;
Syllabus
  • Sources and detectors of light and other types of radiation.
  • Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  • Signal digitization and related protocols, norms and interfaces.
  • Sources of noise and methods of its suppression.
  • Optical system and its components, image formation in optical systems, microscopes and telescopes.
  • Optical errors and their correction.
  • Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  • Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  • Automation of image data acquisition.
Literature
  • RUSS, John C. The image processing handbook [4th ed.]. 4th ed. Boca Raton: CRC Press. 732 s. ISBN 0-8493-1142-X. 2002. info
  • Image sensors and signal processing for digital still cameras. Edited by Junichi Nakamura. Boca Raton, FL: Taylor & Francis. 336 s. ISBN 0849335450. 2006. info
  • KOZUBEK, Michal. Image acquisition and its automation in fluorescence microscopy. In From cells to proteins: Imaging nature across dimensions. Dordrecht: Springer. p. 227-270. NATO Science Series. ISBN 1-4020-3615-9. 2005. info
Teaching methods
Lectures followed by demonstrations of real acquisition devices, both consumer and scientific.
Assessment methods
Lectures in English, study materials in English. Final written exam, no materials allowed.
Language of instruction
English
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (recent)