Visualizing the discrete fourier transform (DFT) in python (tutorial): Part 4
This video series shows how the Python programming language can be used to visualize the discrete fourier transform (DFT)
Part 1:
Introduction and showing how the DFT can be used to represent an image in frequency space.
We then show how adding up individual basis images with the appropriate amplitude and phase (from the DFT) reconstructs the original image
Part 2:
Looking at different ways in which the image can be "compressed" by reducing the amount of information in both the original image or in the DFT.
Part3:
Constructing a block-based DFT in which the original image is split into blocks and transformed.
Part 4:
We compare the block based transform to the full DFT and show that using a block-based approach can lead to much better image compression.
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