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Lecturer(s)
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Bartl Eduard, doc. RNDr. Ph.D.
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Trnečková Markéta, Mgr. Ph.D.
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Janoštík Radek, Mgr. Ph.D.
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Course content
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1. Image representation. Sampling and quantization. Fourier transform. Shannon sampling theorem. Alias, antialiasing. 2. Human illumination and color perception. Color models. 3. Raster image representation. Image compression. Image formats. 4. Image enhancement in the spatial domain. Look-up table. Linear, logarithmic and exponential transformation, gamma correction. Thresholding, adaptive thresholding. Histogram processing. Histogram equalization. 5. Algorithms for drawing straight lines and circles. DDA algorithm. Bresenham algorithm. 6. Area-filling algorithms. Scanline filling algorithm. Seed filling algorithm. 7. Clipping algorithms. Cohen-Sutherland algorithms. Cyrus-Beck algorithms. 8. Algorithms for drawing curves.
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Demonstration
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Learning outcomes
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The students become familiar with basic concepts of computer graphics.
2. Comprehension. Understand basic concepts of computer graphics.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral exam, Written exam
Active participation in class. Completion of assigned homeworks. Passing the oral (or written) exam.
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Recommended literature
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John F. Hughes, Andries van Dam, Morgan McGuire, David F. Sklar, James D. Foley, Steven K. Feiner, Kurt Akeley. Computer Graphics: Principles and Practice (3rd Edition).
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R. C. Gonzalez, R. E. Woods. (2002). Digital Image Processing. Pearson Prentice Hall, New Jersey.
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Steve Marschner, Peter Shirley. (2015). Fundamentals of Computer Graphics 4th Edition. A K Peters/CRC Press.
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W. Burger, M. J. Burge. (2008). Digital Image Processing: An Algorithmic Introduction Using Java.
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W. K. Pratt. (2001). Digital image processing, Third edition. Willey-Interscience, New York.
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Žára, J., Beneš, B., Sochor, J., Felkel, P. (2004). Moderní počítačová grafika, 2. vyd. Brno, Computer Press.
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