Hamming filter to reduce ringing artifact in image
I have a low-resolution image (sLR) which is generated by selecting the central part of the reference high-resolution image (sHR) in the frequency (k-space) domain in row-direction. When I zero-pad this low-resolution image in frequency-domain, I get ringing artifact in the spatial domain as it is expected. I try to remove this artifact by filtering the image using Hamming window. Please see my code below. I have doubts about applying fft and ifft to the image and also filtering process, and I would be thankful if someone could please review my code. My second question is when I use iffft, the output image usually has negative intensities. For further processing in the Spatial domain, is that okay if I normalize the image intensity in a way that the minimum intensity of the image is 0? or should I use the absolute of the image? % sHR: HR reference image n = size(sHR,1); kspHR = fftshift(fft(sHR,n,1),1)/n; % HR image in k-space % Generating LR image (LR in row-direction) kspLR = kspHR((n/2)-(n/4)+1:(n/2)+(n/4),:); sLR = real(ifft(ifftshift(kspLR,1),n,1)))*n; % this image has negative intensity values? % Zero-padding a = floor(size(kspLR,1)/2); kspZP = padarray(kspLR, a ,'both'); sZP = real(ifft(ifftshift(kspZP,1),n,1)))*n;% image with Ringing artifact % Apply Hamming filter to Zero-padded kspace image (kspZP) [r,c]=size(abs(kspZP)); w = hamming(r); W = repmat(w,[1,c]); kspHM = W.*kspZP sHM = real(ifft(ifftshift(kspHM,1),n,1)))*n; % Filtered image in spatial domain
Prashant Kumar answered .
2025-11-20
load penny; sHR = -del2(P); subplot(1,2,1); imagesc(sHR); colormap copper shading flat axis equal % sHR: HR reference image n = size(sHR,1); kspHR = fftshift(fft(sHR,n,1),1)/n; % HR image in k-space % Generating LR image (LR in row-direction) kspLR = kspHR((n/2)-(n/4)+1:(n/2)+(n/4),:); % ZP'd lr beta = 4; % roughly equivalent to Hann w = kaiser(size(kspLR,1),beta); % wKspLR = w .* kspLR; % may work directly if you have R2016b or later. wKspLR = bsxfun(@times, w, kspLR); % continue onwards... a = floor(size(wKspLR,1)/2); wKspZP = padarray(wKspLR, a ,'both'); wsZP = real(ifft(ifftshift(wKspZP,1),n,1))*n; subplot(1,2,2); imagesc(wsZP); shading flat axis equal
As for the negative intensity question... a lot depends on how you want to process the image afterwards. Maybe someone else in the community can comment on that.