In this paper, the wavelet threshold denoising method was used and combined into the FBP algorithm to reconstruct the
imaging. To overcome the drawbacks of the traditional wavelet threshold functions, an improved wavelet threshold
function was proposed, and to improve the reconstruction effect of image, the shift-invariant method was coupled into
the improved wavelet threshold function. To verify the feasibility of the improved wavelet threshold function combined
with shift-invariant method, the simulation experiments of the standard brain phantom were performed by using the FBP
algorithm based on different wavelet threshold functions at the software platform of MATLAB. In addition, the peak
signal-to-noise ratio (PSNR) and mean-square-error (MSE) values of different methods were computed. Experimental
results show that, compared with traditional wavelet threshold functions, the image reconstruction based on the FBP of
the improved wavelet threshold function combined with shift-invariant method has better reconstruction effect. Among
the SL, RL, and Hann filters for the FBP of the improved wavelet threshold function combined with shift-invariant
method, the PSNR value based on RL filter was increased 38.7%, and the MSE value was increased 82%.
Keywords: image reconstruction, filtered back-projection algorithm, wavelet threshold denoising.