A Novel Model for Combining Projection and Image Filtering Using Kalman and Discrete Wavelet Transform in Computerized Tomography

This paper presents a novel model for combining projection and image filtering in computerized tomography. First, it is used an a priori one-dimensional projection filtering, through an extended Kalman filter with joint estimation. Then, the reconstructed images, obtained filtered backprojection algorithms (including the use of Hamming windows), are filtered using the two-dimensional DWT and wavelet thresholding, a non-linear technique. Experiments considering only one filtering stage (a priori 1-D filtering or 2-D DWT image filtering) show images with significant higher noise levels and the combination showed great noise reduction. The obtained results lead to the conclusion that the proposed combining model is a valid and interesting tool for tomographic image analysis.