Fft-based methods rely on the assumption that ring artifacts are corresponding to high-frequency components in the Fourier domain. As a result, they can be removed by damping these components. The following methods are similar to the preprocessing fft-based methods. However, they work on reconstructed images instead of sinograms where the polar transform is used to convert ring artifacts to stripe artifacts.
Using the Fourier transform
Code
sarepy.post.ring_removal_post.ring_removal_based_fft
How it works
Input image is transformed into polar coordinates. The Fourier transform is applied to the result. A 1D low-pass window is multiplied with the row corresponding to the zero frequency in the vertical direction and its neighbors to remove the stripes. The resulting image is transformed into Cartesian coordinates.
How to use
-- The u parameter controls the strength of the cleaning capability. Smaller is stronger. Recommended starting value: 30. -- The n parameter defines the shape of the low-pass filter. It's an insensitive parameter. Recommended value : 8. -- The v parameter allows to select how many rows around the zero-frequency row to be multiplied with the low-pass window. Larger v increases void-center artifacts. Recommended value: 1. -- The pad parameter is needed to reduce the side effects of the Fourier transform.
Using the Fourier transform and wavelet decomposition
Code
sarepy.post.ring_removal_post.ring_removal_based_wavelet_fft
How it works
It's very similar to the fft-based method. The improvement is that the polar transformed image is decomposed using the wavelet transform then the low-pass filter is applied to each of the decomposed image.
How to use
-- The level parameter controls the decomposition level. Higher "level" means stronger cleaning capability. It is because applying the low-pass filter at a deeper level (corresponding to a smaller-size image) results in stronger impact to the recombined image. -- The sigma parameter also controls the strength of the cleaning capability. Larger is stronger, but also increases void-center artifacts. -- The order parameter is insensitive. Recommended value: 8. -- The pad parameter is needed to reduce the side effects of the Fourier transform.