R-L-MS-L Filter Function for CT Image Reconstruction
Abstract: In X-ray computer
tomography (CT), convolution back projection is a fundamental algorithm for CT
image reconstruction. As filtering plays an important part in convolution back
projection, the choice of filter has a direct impact upon the quality of
reconstructed images. Aim at improving reconstructed image quality, a new mixed
filter based on the idea of “first weighted average then linear mixing” is
designed in this article, denoted by R-L-MS-L. Here, R-L filter is relied on to
guarantee the spatial resolution of reconstructed image and S-L filter is
processed via 3-point weighted averaging to improve the density resolution,
thus enhancing the overall reconstruction quality. Gaussian noise of different
coefficients is added to the projection data to contrast the noise performance
of the new and traditional mixed filters. The simulation and experiment results
show that the new filter is better in anti-noise performance and produces reconstructed
images with notably improved quality.
Author: Huiling Hou, Mingquan
Wang, Xiaopeng Wang
Journal Code: jptkomputergg160168
