基于广义变分正则化的闪光照相图像重建算法

 针对闪光照相图像信噪比低的特点，提出了一种基于广义变分正则化的图像重建算法，该方法采用p-范数取代目前广泛采用的全变分范数作为正则项，构造了用于图像重建的展平泛函，将图像重建问题转化为目标泛函最优化问题，采用固定点迭代法求解图像重建的最优解。数值计算结果表明，该算法在重建过程中能够有效抑制图像噪声，并加大对图像边缘的保持能力，从而提高了图像重建质量，是一种有效且性能优良的闪光照相图像重建算法。

Generalized variation-based regularization algorithm for image reconstruction in high energy X-ray radiography

According to the characteristics of flash radiographic image with low signal-to-noise ratio, a generalized variation(GV) regularization based image reconstruction algorithm is proposed. In the new algorithm, p-norm is used as regularized term instead of total variation(TV) norm in widely-used TV-based image denoising methods. Then a smoothing functional is constructed for image reconstruction. Thus, the problem of image reconstruction is transformed to a problem of functional minimization. A nonlinear partial differential equation(PDE) is deduced from the new image reconstruction model. To solve the nonlinear PDE, fixed point iteration(FPI) scheme is introduced to linearize the PDE, ensuring the stability and convergence of regularized solution. Numerical results show that, compared with T