Flash photography object regularization reconstruction method based on truncated singular value and total variation

Abstract

The invention discloses a flash photography object regularization reconstruction method based on a truncated singular value and total variation. The flash photography object regularization reconstruction method includes: (1) obtaining flash photography imaging negative film information through a forward-direction photon transport program; (2) obtaining spatial distribution and geometric parameters of flash photography object linear coefficients through a truncated singular value method; and (3) obtaining the spatial distribution and the geometric parameters of the flash photography object linear coefficients through a total variation regularization method. The flash photography object regularization reconstruction method can effectively reconstruct flash photography object linear absorption coefficients, has high calculation accuracy, has clear resolution at junction of object internal materials simultaneously, has high edge fidelity ability, and meets engineering requirements.

Description

technical field [0001] The invention belongs to the technical field of photon imaging, and relates to a flash photography object reconstruction method, in particular to a flash photography object regularization reconstruction method based on truncated singular value and total variation. Background technique [0002] High-energy flash photography uses high-energy rays to penetrate the object and image it. In the high-energy flash photography system, after the electrons are accelerated by the linear induction accelerator, they hit the target to generate high-energy (MeV) photons, which are used to irradiate the object, and the high-energy photons are transported in the object and interact with it, such as Compton scattering, electron pair effect and photoelectric effect, etc., finally penetrate the object and image it on the film. The amount of scattered radiation is deducted by certain equipment, and the physical and geometric properties of the object are deduced by studying...

AI Technical Summary

Problems solved by technology

The traditional least squares algorithm can guarantee the physical understanding of the reconstruction system. However, in the flash photography system, the photons are scattered with the photographic device. This negative film brings serious scattering noise, which not only reduces the contrast of the image, but also reconstructs the image during the inversion process. Severe Oscillations in Results

Tikhonov added a penalty regularization term with regularization parameters on the basis of least squares. Although it can suppress noise, the penalty term is based on the two-norm, which seriously smooths the boundary information of the reconstructed object and gives the edge band to blur

Landweber iterative regularization does not use some complex criteria to determine regularization parameters like Tikhonov, but uses the reciprocal of the number of iteration steps as the regularization parameter, which greatly reduces the amount of calculation of the system. However, the Landweber iterative regularization algorithm appears semi-convergent. When the number of iterations reaches a certain number, the calculation of the system converges, and as the number of iterations increases, the system tends to diverge

Images