标题： 基于压缩测量的箱约束全变分正则化水平集估计 显示英文标题

标题： Level Set Estimation from Compressive Measurements using Box Constrained Total Variation Regularization

摘要： 从测量中估计信号的等高线是一个在多个领域中出现的任务，包括医学成像、天文学和数字高程映射。 受在某些情况下可能无法获得准确和完整的信号测量的启发，我们在此研究了一种从高度不完整的测量中估计信号等高线的简单方法，这些测量可能还被加性噪声所污染。 所提出的方法基于箱约束全变分（TV）正则化。 我们通过几个模拟示例展示了我们方法的性能，相对于现有最先进的从压缩测量中估计等高线的技术。 显示英文摘要

摘要： Estimating the level set of a signal from measurements is a task that arises in a variety of fields, including medical imaging, astronomy, and digital elevation mapping. Motivated by scenarios where accurate and complete measurements of the signal may not available, we examine here a simple procedure for estimating the level set of a signal from highly incomplete measurements, which may additionally be corrupted by additive noise. The proposed procedure is based on box-constrained Total Variation (TV) regularization. We demonstrate the performance of our approach, relative to existing state-of-the-art techniques for level set estimation from compressive measurements, via several simulation examples.