If you do want to do noise reduction, there are plenty of filters to choose from, from the easy box filter and median filter, to better but more complicated filters like bilateral and Savitzky-Golay, to even better and even more complicated like BM3D, non-local means, K-SVD, K-LLD, etc. I'd start simple and move on up to the better noise reduction filters until you get a level of noise reduction that you can live with. If I had to take a guess I'd say a Savitky-Golay filter might give you a acceptably smoother filter without too much blurring. Let me know if you (or anyone else) wants a demo of a 2D Savitzky-Golay filter (it requires the Signal Processing Toolbox).
Question
I have an almost urgent problem to solve. I have a 2 dimensional 152x2000 matrix, B. We can say time domain signal or image. I have to filter, remove(supress) unwanted like noise parts and improve the image(2 dimensional signal). It can be thought that focusing to the high intensity part of the image. This is the image I have by imagesc abs of B; Finally, I want to get an image only the circle like shape with yellow and red colours. I want to remove the other light blue pixels(signals). I want to filter this image or signal matrix by filtering along two dimensions seperate and orderly. If I say approx. the middle of this circle like shape image is at (29,1334) and then when I plot of abs of B(signal matrix) along 29th row, this is the result ; When I plot of abs of B along 1334 column, the result is ; According to these all info, which best filter along row and column has to implemented ? Bandpass ? , how, could you write the necessary code for the best filtering along two dimensions orderly ? Any fast help greatly appreciated :)
Expert Answer
John Michell
PhD Expert
Answered Aug 13, 2026
If you want to extract the bright section, why are you talking about filters like band pass filters? Just threshold it.
% Find out where it's dark/dim. binaryImage = grayImage < 1.5; % Blacken out where it's below the threshold. grayImage(binaryImage) = 0; imshow(grayImage, []);
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