This approach will inherently have the ringing; FFT is really not meant for local features. STFT may be a more interesting approach. Anyhow, I ran something li

This approach will inherently have the ringing; FFT is really not meant for local features. STFT may be a more interesting approach. Anyhow, I ran something like the following in Matlab for testing upsampling 4 pixels to 8 pixels: fft_mx = fft( eye(4) ); #forward FFT transform matrix fft_mx = padarray( fft_mx, [2 0], 0, 'both' ); #pads result vector with zeroes fft_iv = ifft( eye(8) ); #inverse FFT matrix abs( fft_iv * fft_mx ) * 2 The result is: 1.0000 0 0 0 0.6533 0.6533 0.2706 0.2706 0 1.0000 0 0 0.2706 0.6533 0.6533 0.2706 0 0 1.0000 0 0.2706 0.2706 0.6533 0.6533 0 0 0 1.0000 0.6533 0.2706 0.2706 0.6533 Basically, your idea (which boils down to an FIR scaler) samples the entire image when resampling. That isn't a very good behavior, IMHO. EDIT: fixed math