Localization microscopy provides valuable insights into cellular structures and is a rapidly developing field. The precision is mainly limited by additive noise and the requirement for single molecule imaging that dictates a low density of activated emitters in the field of view. In this paper we present a technique aimed for noise reduction and improved localization accuracy. The method has two steps; the first is the imaging of gold nanoparticles that labels targets of interest inside biological cells using a lock-in technique that enables the separation of the signal from the wide spread spectral noise. The second step is the application of the K-factor nonlinear image decomposition algorithm on the obtained image, which improves the localization accuracy that can reach 5nm and enables the localization of overlapping particles at minimal distances that are closer by 65% than conventional methods.