Enhanced Nanoparticle Detection Using Momentum-Space Filtering for Interferometric Scattering Microscopy (iSCAT)

Interferometric scattering microscopy (iSCAT) is a powerful tool for single-particle detection. However, the detection sensitivity is significantly limited by high-frequency noise. In this paper, we have proposed a novel method leveraging frequency component analysis in the Fourier domain to enhance interference patterns, thus efficiently improving the detection accuracy. The bright–dark rings momentum feather has been effectively restored by a combined filter for high-frequency noise and aperture attenuation. The value of the structural similarity index measure has been improved from 0.73 to 0.98. We validate this method on gold nanoparticle samples. The results demonstrate its great potential to advance single-particle tracking by enhancing background suppression in iSCAT applications.