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Mixed order regularization method applied to weakening step effect in image reconstruction

A technology of staircase effect and image reconstruction, applied in 2D image generation, image generation, image data processing and other directions, can solve problems such as staircase effect, and achieve the effect of strengthening retention, improving imaging quality, and reducing staircase effect.

Pending Publication Date: 2019-09-10
HENAN NORMAL UNIV
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Problems solved by technology

However, the TV regularization method produces a severe staircase effect

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  • Mixed order regularization method applied to weakening step effect in image reconstruction
  • Mixed order regularization method applied to weakening step effect in image reconstruction
  • Mixed order regularization method applied to weakening step effect in image reconstruction

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[0031] A mixed-order regularization method applied to weakening the step effect in image reconstruction of the present invention will be described with reference to the drawings and embodiments.

[0032]The present invention aims to solve the problem that the edge of the reconstructed image has an obvious step effect when the TV regularization method is used to reconstruct the image. On the basis of retaining the data fidelity term in the original TV regularization method, the present invention uses a mixed-order regular term to replace the original regular term with only first-order derivative. This method introduces a second-order derivative term based on the original TV regularization first-order derivative term, and applies a weight factor in front of the first-order derivative term and the second-order derivative term respectively. By adjusting the weight factor to control the weight between the first-order derivative item and the second-order derivative item, the purpose...

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Abstract

The invention discloses a mixed order regularization method applied to weakening a step effect in image reconstruction, and the method comprises the steps: regarding an electrical impedance tomographyproblem as solving a linear uncertainty problem, and determining an objective function, wherein the reconstruction method comprises the steps of obtaining a relative boundary measurement value voltage and a Jacobian matrix required by reconstruction; converting the nonlinear inverse problem of the electrical impedance tomography into a linear inverse problem; determining an objective function, and minimizing the objective function; updating the solution according to the derived dual form; judging whether iteration is finished or not; and according to the optimal gray value obtained through solving, carrying out imaging by using a square grid division method. Retention of sharp edges of the reconstructed image and reduction of the step effect are taken into account at the same time, and the applicability of the algorithm and the quality of the reconstructed image are improved.

Description

Background technique [0001] The invention relates to an image reconstruction method of electrical impedance tomography, in particular to a mixed-order regularization method applied to weakening the step effect in image reconstruction, and belongs to the technical field of electrical tomography. Background technique [0002] Electrical Tomography (ET) appeared in the late 1980s and is an important branch of process tomography. It images the electrical property distribution information of the medium in the measurement area based on boundary measurements. Electrical tomography technology mainly includes electrical impedance tomography (Electrical Impedance Tomography, EIT), electrical resistance tomography (Electrical Resistance Tomography, ERT), electrical capacitance tomography (Electrical Capacitance Tomography, ECT) and electromagnetic tomography (Electrical Magnetic Tomography, EMT). This technology has the advantages of safety, low cost, high speed, no invasion, no ra...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00
CPCG06T11/006G06T11/003G06T2211/424
Inventor 施艳艳张旭王萌
Owner HENAN NORMAL UNIV
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