标题： 基于部分非相干光的二次压缩感知的稀疏性超分辨率成像 显示英文标题

标题： Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing

摘要： 我们证明，给定图像稀疏性的先验知识，仅此而已，可以恢复由部分空间非相干光承载的亚波长光学图像，无论是从远场还是从模糊图像中。 该重建方法依赖于最近展示的基于稀疏性的亚波长成像。 然而，对于部分空间非相干光，测量与图像之间的关系是二次的，产生不符合以前使用的技术的非凸测量方程。 因此，我们展示了新的算法方法，称为二次压缩感知，可以应用于涉及从部分相关测量中恢复信息的其他问题范围，包括当相关函数具有局部依赖性时。 具体到显微镜，这种方法可以很容易地扩展到白光显微镜，只需额外了解光源光谱。 显示英文摘要

摘要： We demonstrate that sub-wavelength optical images borne on partially-spatially-incoherent light can be recovered, from their far-field or from the blurred image, given the prior knowledge that the image is sparse, and only that. The reconstruction method relies on the recently demonstrated sparsity-based sub-wavelength imaging. However, for partially-spatially-incoherent light, the relation between the measurements and the image is quadratic, yielding non-convex measurement equations that do not conform to previously used techniques. Consequently, we demonstrate new algorithmic methodology, referred to as quadratic compressed sensing, which can be applied to a range of other problems involving information recovery from partial correlation measurements, including when the correlation function has local dependencies. Specifically for microscopy, this method can be readily extended to white light microscopes with the additional knowledge of the light source spectrum.