面向全变差正则化反问题的离网格算法
Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems
AI总结：
本文提出一种离网格算法，通过迭代构造简单多边形指示函数的线性组合来求解全变差正则化线性反问题，克服了传统方法依赖固定网格的局限。
摘要：
我们提出了一种以离网格方式求解带总（梯度）变差正则化的线性反问题的算法。与大多数现有方法在固定网格上产生分段常数近似解不同，我们的方法利用了解的结构，并迭代地构造简单多边形指示函数的线性组合。
英文摘要：
We introduce an algorithm to solve linear inverse problems regularized with the total (gradient) variation in a gridless manner. Contrary to most existing methods, that produce an approximate solution which is piecewise constant on a fixed mesh, our approach exploits the structure of the solutions and consists in iteratively constructing a linear combination of indicator functions of simple polygons.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
