Introduction to the Fourier transform for image processing (2001)
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Re: Introduction to the Fourier transform for image processing (2001)
#2This is a bit out of context but nonetheless, it's inspiring: https://www.jezzamon.com/fourier/
Spectrograms and fourier transforms can also be applied to making music through diffuse AI. https://www.riffusion.com/about
Re: Introduction to the Fourier transform for image processing (2001)
#3This is a bit out of context but nonetheless, it's inspiring: https://www.jezzamon.com/fourier/ Spectrograms and fourier transforms can also be applied to making music through diffuse AI. https://www.riffusion.com/about
Beautifully done. God I wish our fourier series lecturer in university motivated the class even a little with illustrations like this. It was 100% derivation and hard maths, no intuition at all
Re: Introduction to the Fourier transform for image processing (2001)
#4I love image FFT! Quite some time ago I implemented it (just a wrapped FFTW) as a plugin for the 'Shake' compositing software that we were using at the time at RSP. It was tricky but incredible fun and like a mini-superpower! People were hand-painting full-colour bokeh images for very fancy defocus effects, among other things. Then Apple bought Shake, and we swapped to Nuke, which also has an FFT built-in which is cool, although last time I looked it didn't do the complex-to-magnitude/phase transformation-and-back which is very handy when working with FTs of pixels.
Re: Introduction to the Fourier transform for image processing (2001)
#5This is a bit out of context but nonetheless, it's inspiring: https://www.jezzamon.com/fourier/ Spectrograms and fourier transforms can also be applied to making music through diffuse AI. https://www.riffusion.com/about
Beautifully done. God I wish our fourier series lecturer in university motivated the class even a little with illustrations like this. It was 100% derivation and hard maths, no intuition at all
Fourier series are kinde of more graspable if they are taught in the context of signal processing --as a nerd I could understand what the frequency domain was, after all, and the maths made sense to me. But when it comes to Laplace Transform in control systems everything became impossible.
Re: Introduction to the Fourier transform for image processing (2001)
#6Earlier quoted context omitted.
Beautifully done. God I wish our fourier series lecturer in university motivated the class even a little with illustrations like this. It was 100% derivation and hard maths, no intuition at all
Fourier series are kinde of more graspable if they are taught in the context of signal processing --as a nerd I could understand what the frequency domain was, after all, and the maths made sense to me. But when it comes to Laplace Transform in control systems everything became impossible.
It’s definitely worth persisting with the Laplace transform.. you get a ton of stuff you can do when you have H(s)=Y(s)/X(s)
Re: Introduction to the Fourier transform for image processing (2001)
#7A better way to eliminate image border effects isnt windowing, but mirrored periodic repetition.
Re: Introduction to the Fourier transform for image processing (2001)
#8A better way to eliminate image border effects isnt windowing, but mirrored periodic repetition.
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Re: Introduction to the Fourier transform for image processing (2001)
#9I always think most of mathematicians is genius. They can hold all concepts and relationships between thems in their mind.
The result is the way they explain concepts to broader audience mostly failed. Abstract nonsense for no purpose.
I'm fine with it... until i see the application to learn more about theory.
Re: Introduction to the Fourier transform for image processing (2001)
#10Earlier quoted context omitted.
Beautifully done. God I wish our fourier series lecturer in university motivated the class even a little with illustrations like this. It was 100% derivation and hard maths, no intuition at all
Fourier series are kinde of more graspable if they are taught in the context of signal processing --as a nerd I could understand what the frequency domain was, after all, and the maths made sense to me. But when it comes to Laplace Transform in control systems everything became impossible.
Brian Douglas produced a decent set of lectures on control systems, I found them to be quite useful during my degree: https://www.youtube.com/@ControlLectures