Micro-CT成像中重建图像的分辨率往往受到X射线的辐射剂量和探测器单元的孔径及大小的限制。在不改变原有成像参数的前提下,通过将重建图像网格的上采样以及重建图像的稀疏性假设先验,提出一种基于全变差模型的Micro-CT图像超分辨率重建模型。基于扩展梯度投影方法,将模型解耦分解为沿保真项的梯度方向下降、TV去噪、两步迭代结果线性组合这3步交替迭代求解。对模拟图像和实际数据进行了仿真测试,并同传统的滤波反投影方法进行了比较。实验结果表明,该算法能够有效提高重建图像的分辨率。

In Micro-CT systems,further improvement of the spatial resolution of the reconstructed images is limited by the X-ray dose level,the pixel pitch,and the aperture of the detector element.In this paper,we study a total variation (TV) based optimization model for Micro-CT reconstruction based on an up-sampling of the reconstruction grid with original detector and X-ray dose.Using an extension of the gradient projection method,an alternating minimization algorithm is employed to solve the corresponding energy function.In the process of the minimization,the treatment is separated into the gradient step of the fit-to-data term,the total variation (TV) denoising,and the specific linear combination of the previous two points.Experiments on simulated data as well as real Micro-CT data are performed.Our results show that the proposed approach can dramatically improve the spatial resolution of the reconstructed images compared to the conventional Filter Back-Projection algorithm.