图像去模糊的l0范数最小化方法

摘要

For classical image deblurring problem, this paper proposes an effective image deblurring algorithm, where an lo-norm regularization is minimized under the constraint that the solution explains the observations sufficiently well. To effectively solve the optimizing problem, two auxiliary variables are introduced and the original problem are divided into two sub-problems which are solved by the alternating direction method. The experimental results indicate that with different size blurry kernels, the proposed algorithm can recover image effectively and steadily for the Gaussian blur and motion blur.%针对经典的图像去模糊问题,提出了一种基于l0-范数约束的图像去模糊算法.该算法结合图像稀疏性的特点,利用l0-范数作为正则项约束,保证了恢复图像的稀疏性要求.为了有效的求解l0-范数优化问题,引入两个辅助变量,将原问题分解为两个子优化问题,并采用交替方向法进行快速求解.实验结果表明,对于不同程度的高斯模糊和运动模糊,该算法都能够得到有效的恢复结果.