Tutorial 41 - Image filtering using Fourier transform in python

This video tutorial explains the use of Fourier transform in filtering digital images. You can learn how to create your own low pass and high pass filters using a few lines of code in Python.

[michaelcapone]

Thank you very much ! I am completing a bachelor in computer science. I took an optional course about images processing and we had a chapter about Fourier transform. Your video was VERY helpful ! Good job !

[nayo]

This is such an amazing channel. I can’t express how grateful I am for the content.

[MC-qzvw]

You are way better at explaining this stuff than most uni teachers. Thanks!

[Yaz]

Thank you so much. Your tutorials are well explained. Please keep posting more videos.
I just have a question. How to determine if an image has a low or high frequency by a value instead of plotting?

[VanNguyen-ypcd]

I dont know why error with a same code:
"dft = cv2.dft(np.float32(img),
cv2.error: OpenCV(4.6.0) :-1: error: (-5:Bad argument) in function 'dft'
> Overload resolution failed:
> - src is not a numpy array, neither a scalar
> - Expected Ptr<cv::UMat> for argument 'src'"

[AjirogheneSunny]

You are such a great tutor. Well explained and understood

[hammadahmed]

Edges are high frequency components. So to detect edges shouldn't we apply high pass filter? Need help..

[Dr.Milk-SN]

After applying Fourier filter, how to save applied images? Converting float 32 to uint8 gives me a weird image.

[-sarthakpandey]

Thank you sir for this video.It is really helpful 🔥

[SuddenWnd]

when doing idft, u can use cv.DFT_SCALE flag to get normalized image
img_back = cv.idft(f_ishift, flags=cv.DFT_SCALE)