Lecture 1 - motivace + matematicky background (konvoluce, Fourier). Download slides L. 1
Lecture 2 - vzorkovani a kvantovani. Download slides L. 2
Lecture 3 - histogram, zmeny jasu a kontrastu obrazu. Download slides L. 3
Lecture 4 - potlaceni sumu. Download slides L. 4
Dale doporucuji shlednout videa:
video 1
video 2
Lecture 5 - detekce hran. Download slides L. 5
Lectures 6, 7 - registrace obrazu, doporucena cetba [3]. Download slides L. 6, 7
Lecture 8 - restaurace obrazu. Download slides L. 8
Lecture 9 - priznaky pro popis a rozpoznavani. Download slides L. 9
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[1] Pratt W. K.: Digital Image Processing (3rd ed.), John Wiley, New York, 2001
[2] Gonzales R. C., Woods R. E., Digital Image Processing (3rd or 4th ed.). Available online at
https://dl.ebooksworld.ir/motoman/Digital.Image.Processing.4th.Edition.www.EBooksWorld.ir.pdf
[3] Zitová B., Flusser J., Image registration methods: a survey. Image and Vision Computing, 21 (2003), 11, pp. 977-1000
[A] Introduction to Object Recognition. Download
[4] Duda R.O. et al., Pattern Classification, (2nd ed.), John Wiley, New York, 2001
[5] Gonzales R. C. et al., Digital Image Processing using MATLAB, Prentice Hall, 2004