To solve the problem of artifact and image degradation caused by incomplete angle projection, this article presents an incomplete angle reconstruction algorithm based on sparse optimization and image optimization criterion (SO-IOC). Firstly, the joint objective function model is established based on the projection sparsity and the natural features of images. Secondly, by means of the idea of alternating direction method of multipliers, the augmented Lagrange method is used to decompose the reconstruction model into simple subproblems and the modified genetic algorithm is used for solving those subproblems. Finally, a multiobjective optimization operation is carried out to coordinate and select the candidate solutions to improve the quality of the reconstructed images. The algebraic reconstruction technique algorithm and the Split Bregman algorithm are compared with the SO-IOC algorithm. In the compared process, the mean relative error and the peak signal-to-noise ratio are used. The experimental results show the SO-IOC algorithm is best among the above three algorithms.

中文翻译：

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具有稀疏优化和图像优化准则的不完全角重建算法

针对不完整角度投影导致的伪影和图像质量下降问题，本文提出了一种基于稀疏优化和图像优化准则（SO-IOC）的不完整角度重建算法。首先，基于投影稀疏性和图像的自然特征建立联合目标函数模型。其次，利用乘法器交替方向法的思想，利用增广拉格朗日法将重构模型分解为简单的子问题，并利用改进的遗传算法求解这些子问题。最后，进行多目标优化操作以协调和选择候选解以提高重建图像的质量。代数重建技术算法和Split Bregman算法与SO-IOC算法进行了比较。在比较过程中，使用了平均相对误差和峰值信噪比。实验结果表明，SO-IOC算法是上述三种算法中效果最好的。