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In this practical you will learn about basic concepts of Fourier theory in digital image processing. You will gain a fundamental and intuitive understanding of the properties and applications of Fourier transforms, learn about convolution operations and their relation to kernels, the convolution theorem and its applications, and the effect of the transfer function of an imaging system on the final image.
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### [Practical 2 – 2D/3D reconstruction](https://edu.nl/tqpf8)
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### [Practical 3 – Introduction to electron tomography](https://edu.nl/7kakp)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.tudelft.nl%2Faj-lab%2Fteaching/master?filepath=binder%2Fhri_practical03.ipynb)
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or visit [https://edu.nl/7kakp](https://edu.nl/7kakp)
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In this practical you will apply your knowledge from the previous practicals to explore 3D reconstruction using tomographic imaging. You will learn about back-projection methods, the importance of sampling and the effect of missing information on image reconstruction.
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This interactive practical uses the following dependencies:
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* [numpy](https://www.numpy.org/)
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