Tracking via Adaptive Image Reconstruction (gredient method and intensity method)

This repository contains the MATLAB implementations of the adaptive imagereconstruction and particle tracking algorithms developed in our study. The code enableshigh-precision tracking of colloidal particles in close proximity by iteratively refiningboth particle positions and shape functions from microscopy images. Two implementations areprovided in MATLAB : a gradient-based method operating on image gradients, andan intensity-based variant operating directly on raw intensity profiles. The algorithms aredesigned to handle strongly overlapping diffraction-limited images and achieve nanometre-scalelocalisation accuracy. Example scripts and documentation are included to reproduce the mainanalysis and figures presented in the associated publication. A minimal demonstration of the algorithm is provided in the folder "Runme", whichcontains a self-contained test example illustrating the core functionality. This repositorydeliberately includes only the essential components of the algorithm, serving as a referenceimplementation accompanying the scientific publication rather than a turnkey analysispackage. Users are expected to develop their own application interface or analysis pipelineto apply the algorithm to custom image data sets. A Python library implementing is available on GitHub: \url{https://github.com/genglaodemao/PyAimRec}.