提出一种基于组合字典和约束优化的图像复原算法.建立表示图像复原问题的约束优化模型,其目标函数由l2保真项和双l1正则项的线性组合构成.利用交替优化技术将模型分解为多个子问题求解,并通过邻近算子解决降噪子问题.实验结果表明,与Oliverira算法和Beck算法相比,该算法的复原速度较快,所得图像质量较好,且复原图像与原始图像的均方误差较小.%According to the existing problems of image restoration in the speed and the quality, this paper presents an image restoration algorithm based on combined dictionaries and constrained optimization. A new constrained optimization model representing the image restoration problem is created. The objective function of it is composed of the fe data fidelity term and dual h regularized term. Then the alternating minimization technology is used to decompose the constrained optimization model into several subproblems to be solved, and the proximal operators are introduced to solve denoising subproblems. Experimental results demonstrate the effectiveness of the presented image restoration algorithm, and compared with some similar state-of-the-art algorithms, it shows better restored results and faster speed.
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