The stripe noise existing in remote sensing images badly degrades the visual quality and restricts the precision of data analysis. Therefore, many destriping models have been proposed in recent years. In contrast to these existing models, in this paper, we propose a nonconvex model with a DC function (i.e., the difference of convex functions) structure to remove the strip noise. To solve this model, we make use of the DC structure and apply an inexact proximal majorization-minimization algorithm with each inner subproblem solved by the alternating direction method of multipliers. It deserves mentioning that we design an implementable stopping criterion for the inner subproblem, while the convergence can still be guaranteed. Numerical experiments demonstrate the superiority of the proposed model and algorithm.

翻译：遥感影像中存在的条带噪声严重降低了视觉质量，并限制了数据分析的精度。因此，近年来提出了多种去条带模型。与现有模型不同，本文提出了一种具有DC函数（即凸函数之差）结构的非凸模型用于去除条带噪声。为求解该模型，我们利用DC结构，应用非精确邻近主化-最小化算法，其中每个内层子问题采用交替方向乘子法求解。值得指出的是，我们为内层子问题设计了可实现的最优性停止准则，同时保证了算法的收敛性。数值实验证明了所提模型与算法的优越性。