Super-resolution of dense nanoscale emitters beyond the diffraction limit using spatial and temporal information

Abstract

We propose a super-resolution technique for dense clusters of blinking emitters. The method relies on two basic assumptions: the emitters are statistically independent and a model of the imaging system is known. We numerically analyze the performance limits of the method as a function of emitter density and noise level. Numerical simulations show that five closely packed emitters can be resolved and localized to a precision of 17 nm. The experimental resolution of five quantum dots located within a diffraction-limited spot confirms the applicability of this approach. Statistical tests validate the independence of our quantum dots separated by nanoscale distances.

Quantum-Optically Enhanced STORM (QUEST) for Multi-Emitter Localization

“…However, due to the usage of normalized correlation functions, it requires little information about emitter properties such as emitter number or brightness. As a first approach, one may use iterative sectioning and include these quantities as fitting parameters, more sophisticated and precise strategies for emitter number estimation exist 33 , 34 and may be optimized for QUEST images. QUEST is therefore similar to localization techniques, but has the additional advantage that it does not require only a sparse subset of all emitters to be active at any time, which promises significantly faster data acquisition rates.…”

Localisation microscopy with quantum dots using non-negative matrix factorisation

“…These techniques take the reappearance of the fluorophores in different frames into account, and allow the localisation of higher densities of ON sources. Among other techniques [8,9] a Bayesian treatment of the sources' position and intensity estimation (3B [10]) has received attention recently. Finally, bSOFI [11] recovers the distribution of fluorophores with high resolution from the analysis of the intensity fluctuation higher order statistics.…”

Dictionary Generation for Sparsity-based Three-Dimensional Super-resolution Microscopy

“…In this way, many localizations can be combined from thousands of frames to generate a single image with resolution beyond the limits imposed by diffraction [1-3]. The need for thousands of frames results in low temporal resolution; we address this problem by utilizing localization methods that can tolerate overlapping images of single molecules [4][5][6][7][8][9][10]. More specifically, one can reconstruct a dense scene by exploiting the mathematical sparsity of the scene [5,9,10].…”