A Novel Model for Combining Projection and Image Filtering Using Kalman and Discrete Wavelet Transform in Computerized Tomography
Marcos A. M. Laia, Alexandre L. M. Levada, Leonardo Castro Botega, Mauricio Fernando Lima Pereira, Paulo Estevão Cruvinel, Álvaro Fabiano Pereira de Macêdo · 2008
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.