A wavelet based multiresolution extended Kalman filter approach to the reconstruction problem of curved ray optical tomography

We present a wavelet based multiresolution extended Kalman filter (EKF) reconstruction approach to curved ray optical tomography. A state variable model describing the tomographic process is set up, and an EKF is applied to the wavelet transformed model to estimate the refractive index distribution of an optically transparent refracting object from noisy optical path-length difference(OPD) data. Preliminary results of reconstructions of a synthetic time-invariant refractive index distribution from OPD data sets of various noise levels are comparable with those obtained from a typically used deterministic approach, the average correction per projection method.