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Basic algorithms for processing grayscale images and the selected color model. Choosing of filters that remove noise from the image. Compression selection depending on the image type. Getting to know the techniques of image segmentation and morphological image processing.

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KrzysiekJa/Digital-Image-Processing-2

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Digital-Image-Processing-2

Technology:

m-scripts typical for MATLAB environment.
Python jupyter notebook (project).

Legend:

0) Making grayscale. Histogram. Operations based on LUT.
1) Different convolutional filtrations.
2) Usage of Fourier transformation and filtering in frequency domain.
3) Noise removal with usage of low pass, high pass filters and kernel filtering.
4) Logical and morfological operations.
5) project -> Hough transform for circle detection

Examples:

Lab 0:



Lab 1:



Lab 2:





Lab 3:





Lab 4:

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Basic algorithms for processing grayscale images and the selected color model. Choosing of filters that remove noise from the image. Compression selection depending on the image type. Getting to know the techniques of image segmentation and morphological image processing.

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