====== BE4M33DZO – Digital Image ======

[[http://www.feld.cvut.cz/cz/education/rozvrhy-ng.B201/public/html/predmety/46/84/p4684806.html|Schedule BE4M33DZO]]
[[https://cw.felk.cvut.cz/upload/|Upload system for student tasks]]

Having the rationalization in mind, the lecture serves three subjects at the same time, i.e., BE4M33DZO 
Digital Image, B4M33DZO Digitální obraz (the same subject in Czech language). Students of the doctoral subject XP33ZVD Základy počítačového vidění (Fundamentals of Computer Vision) visit the lecture as well. 

We lecture the subject in English most of the time following the FEE CTU rule stating that if there is a single student in the audience who does not understand Czech, the lecture is in English. If there are only Czech speaking students at the lecture, we will lecture in Czech (Václav Hlaváč) or Slovak (Radoslav Škoviera).


===== Course objective  =====
The course teaches how to represent, process, and interpret 2D image on a computer. The first part of the course will be focused on image processing taken similarly as in signal processing, i.e. without interpretation. We will explain image acquisition, linear and non-linear pre-processing, and image compression. In the second part, we will teach students the segmentation and registration methods for 2D images. The gained knowledge will be applied to practical examples in exercises so that students will gain practical experience with the topic. 


===== Required prior knowledge  =====
 It is assumed that students of this course have a working knowledge of mathematical analysis, linear algebra, probability theory and statistics. In addition, basic programming skills, mainly in MATLAB, are expected. This master subject should not repeat the knowledge, which was taught in the Open informatics study program in bachelor studies. The subject would be too shallow otherwise.

It could happen that some students did not study the topics, which are considered a prerequisite of the subject Autonomous robotics. They have to study or refresh their knowledge on their own. Some other knowledge/skills might be useful in the subject labs.

I offer students the aid to refresh their knowledge by providing them presentations related to the topic. 


^Author ^ Presentation and the link to it ^
| V. Hlaváč | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/05Mathematics/02ProbabStatRehersalEn.pdf|Probability and statistics, rehearsal]] |
| V. Hlaváč | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/05Mathematics/31LeastSquares.pdf|Least squares]] |

===== Lectures: Wednesdays 9:15-10:45 =====
Remote lecture Microsoft Teams, Microsoft Teams, From September 30, 2020, I lecture in a new MS Team joined for all three subjects, [[https://teams.microsoft.com/l/channel/19%3a6d0f8b46147f4b9a8a276723fd2ce5db%40thread.tacv2/General?groupId=92d413b4-d1aa-4866-9556-528d755dc10f&tenantId=f345c406-5268-43b0-b19f-5862fa6833f8|channel]]. All students registered for these three subjects have access to this channel.

Lecturer: [[http://people.ciirc.cvut.cz/hlavac//|Václav Hlaváč]], [[http://people.ciirc.cvut.cz/skovirad/|Radoslav Škoviera]] (will lecture in an extraordinary case or if Václav Hlaváč is traveling or sick.

Workload: 2 h lecture + 2 h exercises/labs + 5 h homework per week. 
Slides for lectures are available in English on http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/ and in Czech on http://people.ciirc.cvut.cz/~hlavac/TeachPresCz/. I usually improve the slides, when I am preparing for a particular lecture. 


^  Week  ^  Date  ^  Topic  ^  Notes  ^
|   1.  | 23.09.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/012IntroDigImProcVsCompVisionEn.pdf|Computer vision. Objects in image. Interpretation.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/014DigitalImageEn.pdf|Digital image, concepts.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/18BrightGeomTxEn.pdf|Brightness transforms.]] | |
|   2.  | 30.09.2020 | Physical image formation and acquisition and radiometric point of view. [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/03GeomOpticsCameraEn.pdf|Optical view.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/02ImageFormationEn.pdf|Radiometric view.]]| Lab 1, Brightness trans. |
|   3.  | 07.10.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/18BrightGeomTxEn.pdf|Geometric transforms. Interpolation.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/05Mathematics/42DynamicProgramming.pdf|Dynamic programming.]] | | 
|   4.  | 14.10.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/21ImagPreprocEn.pdf|Spatial domain image processing. Convolution, correlation. Noise filtration.]] | Lab 2, seam carving, dynamic programming | 
|   5.  | 21.10.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/12FourierTxEn.pdf|Fourier transform. Sampling theorem.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/13FourierFiltrationEn.pdf|Frequency filtering. Hommomorphic filter.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/25ImagRestorationEn.pdf|Image restoration.]] | |
|   6.  | 28.10.2020 | Public holiday. No lecture. | |
|   7.  | 04.11.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/22EdgeDetectionEn.pdf|Edge detection. Scale space. Canny detector.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/23InterestPointsEn.pdf|Interest points/regions detection.]] | Lab 3, HDR |
|   8.  | 11.11.2020 | Image segmentation - [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/15ImageAnalysis/32-02SegmentationTaxon+Thresh.pdf|thresholding]], [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/15ImageAnalysis/32-04SegmentationSpatialCoherence.pdf|k-means]], [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/31PattRecog/52UnsupervLearning.pdf|EM algorith]] | |
|   9.  | 18.11.2020 | Image segmentation - [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/15ImageAnalysis/32-08SegmentationGraphBased.pdf|Graphs, graph algorithms]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/15ImageAnalysis/32-08SegmentationGraphBased.pdf|Segmentace hledáním maximálního řezu v grafu]]. | Lab 4, segmentation |
|  10.  |  25.11.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/15PCA.pdf|Principal component analysis.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresCz/11DigZprObr/14WaveletsCz.pdf|Wavelets.]] | |
|  11.  | 02.12.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/15ImageAnalysis/54ImageRegistrationEn.pdf|Image and object registration. ]]  | Lab 5, Registration |
|  12.  | 09.12.2020 | Mathematical morphology[[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/71-3MatMorpholBinEn.pdf|- for binary images.]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/71-06MatMorfolGrayEn.pdf|- for grayscale images.]] | Lab 6, Image restoration |
|  13.  | 16.12.2020 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/04ColorImagEn.pdf|Color images and their processing.]] | |
|  14.  | 06.01.2021 | [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/81ImageCompressionEn.pdf|Image compression, ]] [[http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/11ImageProc/85VideoCompress.pdf|video compression.]] | |

===== Labs =====

Instructors: [[http://people.ciirc.cvut.cz/skovirad/|Radoslav Škoviera]] (vedoucí cvičení), [[https://www.ciirc.cvut.cz/people/people-list/?uid=fialado1/|Dominik Fiala]], [[http://people.ciirc.cvut.cz/kucerjul/|Júlia Škovierová]].

Details about laboratory and seminars could be found in section [[https://cw.felk.cvut.cz/doku.php/courses/be4m33dzo/tutorials|labs]].

**Warning**: According to the //CTU Study and Examination Regulations//, attending lectures is optional. To attend the exercises, however, we require theoretical knowledge of the practiced issues (according to the exercise program), which will be taught in previous lectures. If the student wants, he/she can supplement the material from the recommended literature before the exercise.

===== Examination and its evaluation =====
  * Only students who obtained the credit for their lab activity are eligible for the examination. 
  * The examination consists of two parts, written and oral exams. The written part checks the global orientation of the student in the subject matter. Students answer typically six questions, which are randomly selected from the [[http://people.ciirc.cvut.cz/~hlavac/teaching/ExamQuestions/B4M33DZO-CollQueEn.pdf|list of questions]]   Questions may be slightly changed till the end of December. The written exam lasts 30 minutes. The written part of the exam yields 30 points at maximum. 
  * The oral part of the exam follows the written part after the written part is corrected by the teacher. The oral part is a discussion of a student and the teacher about a scientific paper of student's choice. The paper has to be from a respected scientific journal, which cannot be older than five years. The paper has to have a relation to the subject and be written in English. The privilege to choose the paper gives the student the opportunity to bring the discussion to the area he has a deeper knowledge. Students come to the exam with a printed version of the paper with her/his handwritten notes made while reading the paper.
  * The list of journals from which the paper can be selected: IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transaction on Medical Imaging, International Journal on Computer Vision, Medical Image Analysis. The Czech Government pays to its universities the electronic access to papers. Use  [[http://www.cvut.cz/informace-pro-studenty/knihovna|CVUT Library ]] or directly at [[https://dialog.cvut.cz/|portál]]. The student has to know the bibliographic information and should write it on the paper front page. 
  * Oral part of the exam follows after correcting tests (written part). 
  * The examination mark is given by the sum of points. Labs (max. 40 points), written part (max. 30 points), and oral exam (max. 30 points). 
  * The maximal number of points is 100. Examination results: A 100-90 points, B 89-80 points, C 79-70 points, D 69-60 points, E 59-50 points, F < 50 points. 
===== Literature =====
  * Šonka M., Hlaváč V., Boyle R.: Image Processing, Analysis and Machine vision, 3rd edition, Thomson Learning, Toronto, Canada, 2007. Asi deset kopií je k dispozici v knihovně Centra strojového vnímání, katedry kybernetiky FEL. Zájemci nechť kontaktují sekretářku Ing. Hanu Pokornou.  
  * Svoboda T., Kybic J., Hlaváč V.: Image Processing, Analysis and Machine Vision -- A MATLAB Companion. Thomson, Toronto, Canada, 1 edition, 2007. About ten copies are available in the library of the Center for Machine Perception, contact Mrs. Hana Pokorná if needed.
  * Szeliski R.: Computer Vision: Algorithms and Application, Springer, Berlin, 2010. 812 p. The book draft is [[http://szeliski.org/Book/|freely available for download]] 
  * Karu Z.Z.: Signals and Systems Made Ridiculously Easy, ZiZi Press, Cambridge, MA, USA, 2001,  ([[https://www.dinx.in/dl/Computer,%20Technology%20and%20Engineering%20eBooks/Books5/Books5/DSP%20Programming/Signal%20and%20Systems.pdf|You can download the scanned copy]]). We recommend this very tiny book not only to all those who did not study the signal theory but also to others who like to reinforce basic knowledge by reading a rather informal book. 
  * Doxiadēs, A. K., Papadimitriou, C. H., Papadatos, A., & Di, D. A. (2009). Logicomix. An Epic Search for Truth. New York: Bloomsbury. 
  * Doxiadēs, A. K., Papadimitriou, C. H., Papadatos, A., & Di, D. A. Logikomiks, Hledání absolutní pravdy, český překlad Dokořán 2012, ISBN: 978-80-7363-401-8  /  336 stran, přeložil Jaroslav Peregrin