径向边缘的伪影是外部CT图像明显存在的缺点。为了抑制外部CT图像径向边缘的伪影,采用加权方向全变差(WDTV)算法计算沿径向和切向方向的局部方向差分,引入两个权重参数对这两个局部方向差分进行加权求和。WDTV算法可以更好地描述外部CT图像梯度模的稀疏性,有效提升重建图像的质量。针对高噪声中子外部CT检测的需求,在WDTV重建模型的框架下,对沿着径向和切向两个方向附近的一定角度范围内分别施加不同的全变差(TV)最小化约束。改进的WDTV算法中TV最小化的作用更明显,具有更强地抑制径向边缘伪影与抗噪声的性能。计算机仿真结果和齿轮冷中子实验结果表明,改进的WDTV重建模型能够更有效地抑制重建图像的噪声,提高重建图像的质量。

The artifacts of radial edges are obvious shortcoming of external CT image. In order to suppress the artifacts of the radial edge of external CT images the weighted directional total variation (WDTV) algorithm is used to calculate the local directional differences along the radial and tangential directions, and two weighted parameters are introduced to carry out the weighted sum of these two local directional differences. The WDTV algorithm can better describe the sparsity of external CT image gradient magnitude and effectively improve the quality of reconstructed image. In order to meet the needs of high-noise neutron external CT inspection, different total variation (TV) minimization constraints are applied in certain angle ranges near the radial and tangential directions under the framework of WDTV reconstruction model. In the improved WDTV algorithm, TV minimization plays a more obvious role and has stronger performance of suppressing radial edge artifacts and anti-noise. The results of computer simulation and gear cold neutron experiment show that the improved WDTV reconstruction model can suppress the noise of reconstructed images more effectively and improve the quality of reconstructed images.