4 ms·
Done since the mid-1960's :) but, nevertheless, always an interesting read! This is classical (as in pre-GPU AI/ML) Image Processing. The reference text book i
by DrNosferatu 4y ago
Done since the mid-1960's :) but, nevertheless, always an interesting read!
This is classical (as in pre-GPU AI/ML) Image Processing. The reference text book in the field, "Digital Image Processing" by Gonzalez et al, shows how to do it: like the pioneers at JPL's Image Processing Laboratory (est. 1965) denoised Mars pictures from the Mariner probes using Frequency Domain methods like the posted article uses - see an example below.
[https://pixelcraft.photo.blog/2021/09/29/the-early-days-of-image-processing-to-mars-and-beyond/ https://pixelcraft.photo.blog/2021/09/29/the-early-days-of-i...]
- DrNosferatu 4y agoSpeaking of which, with the advent of AI/ML methods, how are Image Processing and Machine Vision courses taught today at Universities? - Has Python or other free languages replaced Matlab yet? - Is Gonzales' course structure still followed somehow?
- jbay808 4y agoIt's so classical, it can be done without a digital computer at all, using fourier optics! The true fastest fourier transform, done at the speed of light. https://en.wikipedia.org/wiki/Fourier_optics https://en.wikipedia.org/wiki/Fourier_optics At the focal plane of a lens, an image is converted into its spatial fourier components. By adding blocking elements at that focal plane (eg. an aperture, or a piece of glass with marker dots), unwanted frequency components can be cut out from the image.
- DrNosferatu 4y agoAha - very nice! My background with Fourier optics is mostly theoretical and the applications numerical. Any references (books or online) exist about physical applications, like the one you mention?