Basic Image Processing Algorithms

Semester
First semester: PPCU, Budapest
Credit
5
Class Type
Lab, Lecture, Practical
Type of the exam
Oral Exam
Prerequisites (if exist)
Comprehensive Exam in Mathematics, Java Programming, Stochastic Signals and Systems
Lecturer
Dr. Dániel Szolgay, assistant professor, PhD
Hours per week
2

Content

The aim of the course is to give an introduction to the basic algorithms used in digital image processing.
Introduction to human vision, 
Digital image representations, sampling, color spaces, interpolation methods
Image properties: contrast, sharpness, histogram
Linear convolution, edge images, noise filtering, image enhancement
Fourier transformation and its applications
Image segmentation, morphological operations
Video processing: segmentation, object detection, object tracking, optical flow
Image compression methods
Shape and feature point descriptors

Required reading

W. K. Pratt: Digital Image Processing, Wiley, 2001.
Richard Szeliski, “Computer Vision. Algorithms and Applications.” Springer, London, 2011
MSeul, L. O’Gorman and M. J. Sammon, “Practical Algorithms for Image Analysis”, Cambridge University Press, Cambridge, 2012

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