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Last update: G_I (15.05.2013)
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Last update: RNDr. Tomáš Holan, Ph.D. (29.10.2019)
Úspěšné absolvování závěrečného testu - řešení zadané úlohy ze zpracování obrazu v Matlabu. |
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Last update: G_I (14.05.2013)
Gonzales R. C., Woods R. E., Digital Image Processing (3rd ed.), Addison-Wesley, 2008 Pratt W. K.: Digital Image Processing (3rd ed.), John Wiley, New York, 2001
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Last update: G_I (14.05.2013)
Matlab basics Fourier transform ( basics: amplitude, phase, real and imaginary part; filtering in frequency domain) Noise removal (noise and its variations, noise parameters, noise removal - convolution filters, frequency based filters, averaging) Edge detection and histogram equalization (Roberts, Sobel, Maar-Hilbert, edge enhancement, histogram equalization) Morphology (erosion, dilatation, opening, closing, object counting, skeletonization) Image registration (correlation, a registration of an affinely transformed image ) Deconvolution (convolution theorem, inverze filtering, Wiener filter, parameter estimation) Classification (Fourier descriptors, feature space, distance matrix, classification, moment invariants) Hough transform Segmentation ( image segmentation, object classification)
Detailed info can be found here http://zoi.utia.cas.cz/teaching. Recomended lectures: NPGR013 (J. Flusser, B. Zitová), NPGR022 (J. Flusser, B. Zitová), a NAIL072 (J. Štanclová). |