Super-resolved image acquisition with full-field localization-based microscopy: Theoretical analysis and evaluation

We analyze and evaluate super-resolved image acquisition with full-field localization microscopy in which an individual signal sampled by localization may or may not be switched. For the analysis, Nyquist-Shannon sampling theorem based on ideal delta function was extended to sampling with unit pulse comb and surface-enhanced localized near-field that was numerically calculated with finite difference time domain. Sampling with unit pulse was investigated in Fourier domain where magnitude of baseband becomes larger than that of adjacent subband, i.e. aliasing effect is reduced owing to pulse width. Standard Lena image was employed as imaging target and a diffraction-limited optical system is assumed. A peak signal-to-noise ratio (PSNR) was introduced to evaluate the efficiency of image reconstruction quantitatively. When the target was sampled without switching by unit pulse as the sampling width and period are varied, PSNR increased eventually to 18.1 dB, which is the PSNR of a conventional diffraction-limited image. PSNR was found to increase with a longer pulse width due to reduced aliasing effect. When switching of individual sampling pulses was applied, blurry artifact outside the excited field is removed for each pulse and PSNR soars to 25.6 dB with a shortened pulse period, i.e. effective resolution of 72 nm is obtained, which can further be decreased.