![]() Here is a simple and effective linear filtering strategy to remove the horizontal line artifact:Įstimate the frequency of the distortion by looking for a peak in the image's power spectrum in the vertical dimension. Plt.imshow(magnitude_spectrumR, cmap='gray') ResR = np.abs(np.fft.ifft2(np.fft.ifftshift(magR))) Magnitude_spectrumB = 20*np.log(np.abs(fshift2)) ![]() Magnitude_spectrumG = 20*np.log(np.abs(fshift2)) Magnitude_spectrumR = 20*np.log(np.abs(fshift1)) My Code: from skimage.io import imread, imsave I have tried HPF, and LPF in Fourier domain, but the results were not good as you can see: My approach is to use Fast Fourier Transform(FFT) to denoise the image channel by channel. My Question is how to denoise the image effectively using FFT without affecting the quality of the image much, somebody told me that I have to suppress the lines that appears in the magnitude spectrum manually, but I didn't know how to do that, can you please tell me how to do it? I have image of skin colour with repetitive pattern (Horizontal White Lines) generated by a scanner that uses a line of sensors to perceive the photo.
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