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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Image Data Processing

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Code Completion Credits Range Language
F7PBBZOD KZ 2 1P+1C Czech
Garant předmětu:
Zoltán Szabó
Lecturer:
Zoltán Szabó
Tutor:
Pavla Suchánková, Zoltán Szabó
Supervisor:
Department of Biomedical Informatics
Synopsis:

The aim of the course is to provide basic knowledge about the principles of the digital image processing process (algorithms - implementation and realization). This goal also includes the issue of digitization and basic methods of image data analysis.

Requirements:

Basic knowledge of working in the Matlab software environment

Syllabus of lectures:

1. Introduction - optics of the eye, Spectral sensitivity of the human eye, Luminance sensitivity of the eye, Contrast sensitivity of the eye, Spatial resolution of the eye, Temporal resolution of the eye, General scheme of the imaging process

2. Halftonning and Dithering, Histogram, Point Operations, Brightness Modification, Contrast Modification, Logarithmic Brightness Transformation, Gamma Correction, Thresholding, Adaptive Thresholding, Bit-Plane Slicing

3. Histogram equalization, Colors, High / True Color, Color model, RGB (A), additive model, CMY - subtractive model, RGB to grayscale conversion, HSV model, HLS model, XYZ chromatic diagram, (CIE) , Gamut

4. General scheme of imaging process, Filtration (selection or sampling) property of Dirac pulse, Linear imaging system, Convolution and correlation in continuous and discrete region

5. Edge finding, Edge, edge point, Category of edge detectors, Gradient image function, Discrete approximation of derivation, Sensitivity of derivative to noise, convolution masks, Laplacian image function, LoG operator, DoG,

6. 2D Fourier transform, Continuous signal sampling, Aliasing, Antialiasing filter, frequency domain filtering

7. Image compression, Redundancy and irrelevance, RLE - run length coding, Huffman coding, 2D DFT, JPEG, BOC vs. ROC

Syllabus of tutorials:

1. Specifics of image information processing in Matlab - Image Processing Toolbox, possibilities of HW cooperation with Matlab in image processing, overview of functions, basic image operations, freely distributable tutorial MIPS

2. Calculation of basic image parameters (mean brightness, min. And max. Brightness, matrix size, number of gray levels, noise types, signal-to-noise ratio SNR, PSNR, root mean square deviation of two images, etc.), image formats in Matlab, experiment on the perception of brightness and contrast

3. Arithmetic and logical operations over the image, conversion characteristics (LUT) - types and implementations

4. Histogram, expansion and alignment of the histogram

5. 2D Fourier transform, 2D convolution (different types of masks), filtering (averaging, median, etc.)

6. Segmentation and geometric transformations

7. Compression of image data and calculation of selected image quality indicators

Study Objective:

Understanding of image processing methods as a generalization of methods for signal processing. Gaining practical experience with digital image processing.

Study materials:

Recommended literature:

[1] Rafael C.Gonzales, Paul Wintz: Digital Image Processing, 2002.

[2] Šonka M., Hlaváč V., Boyle R.: Image Processing, Analysis and Machine vision, 3rd edition, Thomson Learning, Toronto, Canada, 2007

[3] Svoboda T., Kybic J., Hlaváč V.: Image Processing, Analysis and Machine Vision - A MATLAB Companion. Thomson, Toronto, Canada, 1 edition, 2007.

Note:
Time-table for winter semester 2023/2024:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
roomKL:B-435
Szabó Z.
10:00–11:50
EVEN WEEK

(lecture parallel1)
Kladno FBMI
Počítačová učebna
Tue
roomKL:B-520
Szabó Z.
08:00–09:50
EVEN WEEK

(lecture parallel1
parallel nr.1)

Kladno FBMI
Lab. umělé inteli. a bioinfor.
Wed
Thu
Fri
Time-table for summer semester 2023/2024:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2023-08-30
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