CTU FEE Moodle
Advanced areas in image and video technology
B232 - Summer 23/24
This is a grouped Moodle course. It consists of several separate courses that share learning materials, assignments, tests etc. Below you can see information about the individual courses that make up this Moodle course.
Advanced areas in image and video technology - B2M37MOT
Main course
| Credits | 5 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | Czech |
| Extent of teaching | 2P+2L |
Annotation
This course focuses on the state-of-the-art techniques for digital image and video technology. These techniques and their applications cover almost all areas of technical professions dealing with human interaction. A significant part of the course is focused on the methods of image signal processing and main hardware and software functional blocks of related imaging systems. The aim of the laboratory exercises is to familiarize with advanced methods for capturing, processing and reproduction of image information. Due to the fast progress in this area, the content of the lectures and exercises is being continuously updated.
Study targets
No data.
Course outlines
1. Linear algebra for multidimensional signal processing, matrix representation of images, spectral representation.
2. Multiscale image processing, pyramidal decomposition, continuous and discrete wavelet transform.
3. Human visual system characteristics and models.
4. Real imaging systems and their transfer characteristics.
5. Modelling of image signals, basic models of noise, methods of image reconstruction, noise reduction.
6. Super-resolution, compressed sensing.
7. High dynamic range (HDR) image acquisition and reproduction.
8. Capturing and processing of images from light-field camera.
9. Parallelization of image processing algorithms, utilization of GPU.
10. Principles of 3D imaging, stereoscopic and volumetric imaging, digital holography.
11. TV systems with high-definition (HDTV, UHDTV), high frame rate (HFR) and a wide color gamut (WCG).
12. Projection technology, recording and reproduction of images in digital cinema (DCI).
13. Colorimetry in image technology and color management.
14. Acquisition and processing of scientific image data in astronomy and biomedicine.
2. Multiscale image processing, pyramidal decomposition, continuous and discrete wavelet transform.
3. Human visual system characteristics and models.
4. Real imaging systems and their transfer characteristics.
5. Modelling of image signals, basic models of noise, methods of image reconstruction, noise reduction.
6. Super-resolution, compressed sensing.
7. High dynamic range (HDR) image acquisition and reproduction.
8. Capturing and processing of images from light-field camera.
9. Parallelization of image processing algorithms, utilization of GPU.
10. Principles of 3D imaging, stereoscopic and volumetric imaging, digital holography.
11. TV systems with high-definition (HDTV, UHDTV), high frame rate (HFR) and a wide color gamut (WCG).
12. Projection technology, recording and reproduction of images in digital cinema (DCI).
13. Colorimetry in image technology and color management.
14. Acquisition and processing of scientific image data in astronomy and biomedicine.
Exercises outlines
1. Matrix representation for multidimensional image signals. Spectral representation of images.
2. Methods for Subjective and objective image quality methods assessment.
3. Image sharpening algorithms.
4. Superresolution (super-resolution) for image post-processing.
5. High dynamic range (HDR) image acquisition and transmission. Semester project assignment.
6. Acquisition and transmission of stereoscopic images.
7. Parallelization of selected image processing algorithms, utilization of GPU.
8. Measurement of transfer characteristics of digital cameras.
9. Measurement of the properties of photographic filters.
10. Measurement of image sensor parameters.
11. Scientific image data acquisition and preprocessing in astronomy and biomedicine.
12. Work on semester projects.
13. Presentation of semester projects.
14. Test, assessment.
2. Methods for Subjective and objective image quality methods assessment.
3. Image sharpening algorithms.
4. Superresolution (super-resolution) for image post-processing.
5. High dynamic range (HDR) image acquisition and transmission. Semester project assignment.
6. Acquisition and transmission of stereoscopic images.
7. Parallelization of selected image processing algorithms, utilization of GPU.
8. Measurement of transfer characteristics of digital cameras.
9. Measurement of the properties of photographic filters.
10. Measurement of image sensor parameters.
11. Scientific image data acquisition and preprocessing in astronomy and biomedicine.
12. Work on semester projects.
13. Presentation of semester projects.
14. Test, assessment.
Literature
[1] Gonzalez, R. C., Woods, R. E., Digital image processing, Upper Saddle River: Prentice-Hall, 2007.
[2] Gonzalez, R. C., Woods, R. E., Eddins, S. L., Digital image processing using MATLAB, Natick: Gatesmark, 2009.
[3] Woods, J. W., Multidimensional signal, image, and video processing and coding, Amsterdam: Academic Press, 2012.
[4] Milanfar, P., Super-resolution imaging, Boca Raton: CRC, 2011.
[5] Bovik, A. C., Handbook of image and video processing, Amsterdam: Elsevier, 2005.
[6] Cristobal, G., Schelkens, P., Thienpont, H., Optical and digital image processing: fundamentals and applications, Weinheim: Wiley, 2011.
[7] Dufaux, F., Pesquet-Popescu, B., Cagnazzo, M., Emerging technologies for 3D video: creation, coding, transmission and rendering, Chichester: Wiley, 2013.
[8] Mrak, M., Grgić, M, Kunt, M., High-quality visual experience: creation, processing and interactivity of high-resolution and high-dimensional video signals, Heidelberg: Springer, 2010.
[9] Reinhard, E., High dynamic range imaging: acquisition, display, and image-based lighting, Burlington: Morgan Kaufmann/Elsevier, 2010.
[10] Poynton, C., Digital video and HDTV algorithms and interfaces, Amsterdam: Morgan Kaufmann, 2003.
[2] Gonzalez, R. C., Woods, R. E., Eddins, S. L., Digital image processing using MATLAB, Natick: Gatesmark, 2009.
[3] Woods, J. W., Multidimensional signal, image, and video processing and coding, Amsterdam: Academic Press, 2012.
[4] Milanfar, P., Super-resolution imaging, Boca Raton: CRC, 2011.
[5] Bovik, A. C., Handbook of image and video processing, Amsterdam: Elsevier, 2005.
[6] Cristobal, G., Schelkens, P., Thienpont, H., Optical and digital image processing: fundamentals and applications, Weinheim: Wiley, 2011.
[7] Dufaux, F., Pesquet-Popescu, B., Cagnazzo, M., Emerging technologies for 3D video: creation, coding, transmission and rendering, Chichester: Wiley, 2013.
[8] Mrak, M., Grgić, M, Kunt, M., High-quality visual experience: creation, processing and interactivity of high-resolution and high-dimensional video signals, Heidelberg: Springer, 2010.
[9] Reinhard, E., High dynamic range imaging: acquisition, display, and image-based lighting, Burlington: Morgan Kaufmann/Elsevier, 2010.
[10] Poynton, C., Digital video and HDTV algorithms and interfaces, Amsterdam: Morgan Kaufmann, 2003.
Requirements
Knowledge of linear algebra, mathematical analysis, and analysis of signals and systems.
Advanced areas in image and video technology - A0M37MOT
| Credits | 5 |
| Semesters | Summer |
| Completion | Graded Assessment |
| Language of teaching | Czech |
| Extent of teaching | 2+2L |
Annotation
This course presents the state-of-the-art techniques for digital image and video technology. These techniques and their applications cover almost all areas of technical professions dealing with human interaction. The content of lectures is being updated rapidly and continuously according to a remarkable progress in this field. The course deals with the principal functional blocks of mentioned systems both hardware and software implemented.
Study targets
Students acquire knowledge in advanced methods and technology in imaging, including image acquisition, reproduction, processing and optical methods for image processing.
Course outlines
1. Introduction, development of image and video technology
2. Problems of real image gathering systems (CCD, CMOS)
3. Digital photography - functional blocks, image processing
4. Imaging systems of cameras and projectors
5. Advanced image compression techniques
6. Advanced image reconstruction techniques
7. Advanced video recording and postproduction techniques
8. Special image reproduction systems, 3D imaging
9. High Definition TV systems (HDTV, UHDTV)
10. Lighting and flash systems - types, characteristics
11. Advanced digital printing techniques, color management
12. Presentation and projection technology
13. Security and surveillance systems
14. Image technology in astronomy and biomedicine
2. Problems of real image gathering systems (CCD, CMOS)
3. Digital photography - functional blocks, image processing
4. Imaging systems of cameras and projectors
5. Advanced image compression techniques
6. Advanced image reconstruction techniques
7. Advanced video recording and postproduction techniques
8. Special image reproduction systems, 3D imaging
9. High Definition TV systems (HDTV, UHDTV)
10. Lighting and flash systems - types, characteristics
11. Advanced digital printing techniques, color management
12. Presentation and projection technology
13. Security and surveillance systems
14. Image technology in astronomy and biomedicine
Exercises outlines
1. Introduction, seminar on laboratory measurements
2. Measurement of camera noise parameters
3. Measurement on security camera system
4. Measurement of resolution of objective lens
5. Measurement in photography studio, characteristics of lighting system
6. Measurement of colorimetric parameters and color management
7. Processing of color images and video in Matlab
8. Implementation of advanced image reconstruction techniques
9. Controlling video camera from Matlab programming environment
10. Evaluation of resolution of objective lens
11. Calculation of correlated color temperature of light sources
12. Lossy compression techniques of image and video
13. Movement detection in video sequences
14. Assessment, project evaluation
2. Measurement of camera noise parameters
3. Measurement on security camera system
4. Measurement of resolution of objective lens
5. Measurement in photography studio, characteristics of lighting system
6. Measurement of colorimetric parameters and color management
7. Processing of color images and video in Matlab
8. Implementation of advanced image reconstruction techniques
9. Controlling video camera from Matlab programming environment
10. Evaluation of resolution of objective lens
11. Calculation of correlated color temperature of light sources
12. Lossy compression techniques of image and video
13. Movement detection in video sequences
14. Assessment, project evaluation
Literature
[1] Gonzales, R. C. Digital image processing, Upper Saddle River : Pearson, 2002.
[2] Bovik, A. Handbook of Image and Video Processing, Elsevier Academic Press, New York, 2005.
[2] Bovik, A. Handbook of Image and Video Processing, Elsevier Academic Press, New York, 2005.
Requirements
see moodle.kme.fel.cvut.cz