Microscopy: Fourier Space (Bo Huang)
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- čas přidán 6. 08. 2024
- Learn more: www.ibiology.org/talks/fourie...
The Fourier transform is intimately associated with microscopy, since the alternating planes occurring in the microscope (focal plane - back-focal plane, etc.) are related to each other by a function very similar to the Fourier transform. This lectures explains the Fourier transform in terms understandable to non-mathematicians, and explains the relations with microscopy. - Věda a technologie
10/10, by far the most intuitive and simple Fourier transform explaination applied in image processing
I cannot believe how amazing this lecturer is to connect the lens and fourier transform, I have learned so much!
Seriously thank you so much for this. I've been trying to understand FT for days and now it finally clicked!
Awesome! Very clear the relationship between focal plane image and Fourier representation! Thank you!
Best lecture to understand the signal processing perspective and Fourier transform of image.
WoW! This is the best explanation of FFT one can find online!
Thanks a lot!
Extremely useful for understanding the concept of cryo-EM. Thank you!
Colleague, You are great! Thank you so much, I've seen almost hundred of movies, tried to read, nothing helped. Thank you so much. You are really great teacher, please, keep teaching.
Thank you very very much!
This was an awsome practical explanation of FT I had ever seen.
This video and the one on Fourier transform by 3blue1brown made my understanding of FFT much clearer. The best explanation. Lots of love and keep up making such content videos!
Love it, I have been seeking a simple explanation to kickoff some intuition. Please keep on doing your amazing work :)
Awesome. The best explanation I find these days.
Bo you are great!
this is the best explanation of this topic I have come across and would absolutely recommend it.
Well done!
Wow...this lecture helps to visualise the concepts of FT ..such an amazing lecture.
Pretty impressed with how much information (a collection of sine waves) can be encoded in a 2d plane via this construction.
This is pure gold man, good job!
fourier transfer of fourier himself is such a nerd thing to do lol, love this lecture Thanks!
Great explanation, very intuitive. A keeper! Thanks!
Great video! It was extremely informative and helpful. Thank you so much.
This was awesome. Thanks!
it is really detailed FT explanation. thanks a lot.
I agree wow, this IS the best description of 2D Fourier!
Great explanation of FT! well done!
The best explanation of fourier transformation.
Thank you for the intuitive explanation about Fourier transform! (So happy to discover this video omg
Let me guess... this kid learned proper English and proper physic. Congrat, another science hero sharing his knowledge with us!
Brilliance, thank you.
Proud of seeing such clear explanation for 2D frequency.
omg, best explanation:)) . i wish you were my professor. clear and simple
Such a great explanation. Thank you very much!
very well explained!
Thank you for the clear explanation!
Mind blowing, outstanding way of explaining ❤
Top class!
great explanation thank you!
Very nice explanation! Good job!
this video is golden.
Really helpful video~ Thanks
Very helpful!
Great explanation!
This is by far the best explanation I’ve found online regarding the frequency domain analysis of 2D signals. Great work!!!!!!!!!
Best video in Fourier transform 👍
simply awesome sir
your a king! cant belive this doesn't have 1M views
Thanks it help me understand what is k-space
Very clear and precise explanation of Fourier Transformation so far. Subscribe!
Simply clever... keep it up...
It's a magnificent explanation, than you!
Very clear concept in physics to connect to maths
A thorough understanding of the amazing fourier transform. The F.T in time will become the most poeerful tool in explaing quantum computing and construction fabric of the universe. It has yet to go in terms of its contibution to mankind.
very well explained！
Incredible video
Isn't there a mistake on 9:27? I think the Fourier image should be rotated on 90 degrees, coz in the direction of x there are many freaquences due to sharp steps.
very intuitive!
Good explanation
Great job
Thank you
First of all, this is a great video! Very insightful. I have a question about x, though. At 12:15, it's said that x=f sin a. Wouldn't this be x=f tan a? For small angles, I understand they'd be approximately equal. Is this done for convenience, then?
I have the same doubt
I am confused there too.
Love this
Thanks!
💯/💯 Thank you so much sir
is the fourier plane the same as the back focal plane of a lense?
Brilliant.
振幅A可以通过点的亮暗在图中表示，那相位phi是怎么在图中表示的呢？
Should it be a cosine at 14:27 (bottom equation) instead of a sine?
i agree with you.
if the phase delay is 2 WAVELENGTH, SIN will give a result 0, NOT A INCREASE OF IN TENSITY.
对我所听过的傅里叶变换的最佳解释！
And at 15:25 I dont think it is Fourier Transform, it is Fourier series!! They are related but not the same!
really thanks
thank you
Good job, man
I might have missed it. Intensity of a point on the Fourier plane represents amplitude, but which visual feature represents phase?
The phase plot isn't shown in this context. The FT plot you see here represents the magnitude; the phase is not easily interpretable.
Great!
can anyone tell me why x = fsinα. is i miss something?
thank you very much . you dont have any idea how is that help me
I had a high expectation at the beginning of this video, but when it goes to Fourier transform into frequency and inverse, I am not learning anything
wow at 10:50 he shows the darkfield image !!!!
very useful
cool
kodous
And at 17:36, he said "from previous slide, k would be f times sine of alpha" but previously he wrote "x = f sin(alpha)"...... listen to yourself professor!
Despite the good parts, flaws are serious to me. In the beginning, the light propagates from the right to the left, but then the opposite in the slide with the portrait of Fourier. The meaning of sample and back focal plane is made confusing. And the definition of alpha is messed up.
9:32
K_max has units of 1/length, by definition, and f*NA has units of length, you cant compare both of them, k_max=k*NA
And and at the very end, he labeled the "sample" with "point spread function", how on earth could a psf be formed on the sample, instead of the image plane, when you were talking about emission??? Dont be disguised by his seeming confidence, the underlying logic was full of holes!!!
I dont like the video especially because he made it very confusing when talking about the image formation with two focal planes. He didnt clearly define k there and I thought it was supposed to be about emission but he made it sound like illumination......
fantastic explanation! thanks!