Abstract
The computed tomography (CT) reconstruction algorithm is one of the crucial components of the CT system. To date, total variation (TV) has been widely used in CT reconstruction algorithms. Although TV utilizes the a priori information of the longitudinal and lateral gradient sparsity of an image, it introduces some staircase artifacts. To overcome the current limitations of TV and improve imaging quality, we propose a multidirectional anisotropic total variation (MATV) that uses multidirectional gradient information. The surrounding rock of coal mining faces uses principles of tomography similar to those of medical X-rays. The velocity distribution for the surrounding rock can be obtained by the first-arrival traveltime tomography of the transmitted waves in the coal mining face. Combined with the geological data, we can interpret the geological hazards in the coal mining face. To perform traveltime tomography, we first established the objective function of the first-arrival traveltime tomography of the transmitted waves based on the MATV regularization and then used the split Bregman method to solve the objective function. The simulated data and real data show that the MATV regularization method proposed in this paper can better maintain the boundaries of geological anomalies and reduce the artifacts compared with the isotropic total variation regularization method and the anisotropic total variation regularization method. Furthermore, this approach describes the distribution of geological anomalies more accurately and effectively and improves imaging accuracy.
Highlights
X-ray computed tomography (CT) has been widely used in medical diagnosis [1,2,3,4] since it was invented in 1973
Direct iterative algorithms are currently widely used in CT, such as the simultaneous algebraic reconstruction technique (SART) [5], algebraic reconstruction technique (ART) [6], and adaptive algebraic reconstruction technique (AART) [7]. ere is a type of iterative algorithm that uses the image gradient sparse a priori information, which is known as total variation (TV) regularization
To take advantage of the multidirectional gradient information and improve imaging accuracy, we propose a multidirectional anisotropic total variation (MATV) and apply it to the tomography of the surrounding rock of a coal mining face. e results of the two examples show the effectiveness of the proposed method
Summary
X-ray computed tomography (CT) has been widely used in medical diagnosis [1,2,3,4] since it was invented in 1973. Wang et al [38] showed that ATV has higher imaging accuracy than ITV Geological anomalies such as faults, collapse columns, and goafs in coal mining faces can affect production efficiency, which is potentially challenging for safe production [39,40,41]. E refracted waves that propagate along the surrounding rock will be generated when the seismic waves are excited in the coal mining face. Erefore, the first-arrival traveltime of the transmitted waves in the coal mining face is the propagation time of the refracted waves in the surrounding rock. To take advantage of the multidirectional gradient information and improve imaging accuracy, we propose a multidirectional anisotropic total variation (MATV) and apply it to the tomography of the surrounding rock of a coal mining face. To take advantage of the multidirectional gradient information and improve imaging accuracy, we propose a multidirectional anisotropic total variation (MATV) and apply it to the tomography of the surrounding rock of a coal mining face. e results of the two examples show the effectiveness of the proposed method
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