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Image Data Processing

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Code Completion Credits Range Language
17KBIZOD Z,ZK 5 8P+8L Czech
Garant předmětu:
Zoltán Szabó
Zoltán Szabó, Jan Tesař
Zoltán Szabó, Jan Tesař
Department of Biomedical Informatics

Continuous image representation, linear 2D systems, 2D spectrum, Digital representation of images, Basic image characteristics: brightness, contrast, resolution, noise, look up tables, histogram, Discrete Fourier transform,

discrete cosine transform, image enhancement, geometric operations, image filtering, morphological operations, image restoration, image segmentation, basic principles of image compression.

Syllabus of lectures:

1.Overview of available resources of image data, image sensing process, cameras, basic scheme of image scanning, digitalization and processing. Different image sensing elements.

2.Special systems EBCCD, EM, PMT, II, ICCD, MCP and their description, applications in biomedical engineering.

3.Image digitalization, quantization, types and features, demonstration on HW for digitalization and microscope.

4.Image as two dimensional matrix of data, 3D contours, basic operations on pixels, pixel connectivity.

5.Arithmetic and logic operations on the image, Look up tables (LUS), histogram, histogram equalization.

6.2D Fourier transformation, 2D convolution, image filtering.

7.Image segmentation, geometrical transformation, basic principles of image compression.

Syllabus of tutorials:

1.Specifications of Image processing in Matlab, Image processing toolbox, basic image procession operations.

2.Computation of basic image parameters (min. and max brightness, size, SNR, etc.)

3.Arithmetic and logic operations on the image, Look up tables (LUS), histogram, histogram equalization.

4.Histogram and operation on the histogram

5.2D Fourier transformation, 2D convolution (different types of masks), image filtering.

6.Image segmentation, geometrical transformation.

7.Image compression.

Study Objective:

The goal of the subject is give the basic principles of image sensing processes including digitalization and further image processing (implementation of basic image processing algorithms)

Study materials:

[1]Gonzales, R.C.: Digital Image Processing using MATLAB, USA, Prentice Hall,2004.

Time-table for winter semester 2023/2024:
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Time-table for summer semester 2023/2024:
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The course is a part of the following study plans:
Data valid to 2024-04-22
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