Abstract
A maximum a posteriori (MAP) estimation based on Bayesian framework is applied to image reconstruction of two-dimensional highly scattering inhomogeneous medium. The finite difference method (FDM) and conjugate gradient (CG) algorithm serve as the forward and inverse solving models, respectively. The generalized Gaussian Markov random field model (GGMRF) is treated as the regularization, and finally the influence of the measurement errors and initial distributions is investigated. Through the test cases, the MAP estimate algorithm is demonstrated to greatly improve the reconstruction results of the optical coefficients.
Highlights
The optical information reconstruction in nonhomogeneous medium exposed to collimated short-pulse irradiation has been a research focus in transient radiative transfer recently
The diffuse optical tomography (DOT) is an emerging technology that can reconstruct the optical properties of internal biological tissues from the measured transient transmittance and reflectance signals at the boundary of tissues
A maximum a posteriori (MAP) estimation based on Bayesian framework algorithm is applied to image reconstruction of twodimensional highly scattering inhomogeneous medium
Summary
The optical information reconstruction in nonhomogeneous medium exposed to collimated short-pulse irradiation has been a research focus in transient radiative transfer recently. It is widely used in many fields, such as nondestructive testing, optical tomography, infrared remote sensing, information processing, combustion diagnosis, biology, and medicine [1,2,3,4,5,6,7]. Among these fields, the diffuse optical tomography (DOT) is an emerging technology that can reconstruct the optical properties of internal biological tissues from the measured transient transmittance and reflectance signals at the boundary of tissues. It offers the significant advantages of both flexibility to geometry and heterogeneity of tissue and is easy to be solved using numerical methods [8]
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