In order to improve the time resolution of super-resolution fluorescent microscopy, the methods of high-density molecule localization have been proposed. Three algorithms based on compressed sensing models, including the interior-point method in the CVX toolbox, the homotopy method, and the orthogonal matching pursuit (OMP) algorithm, are investigated. We compare the identified density, localization precision, and execution time by using these algorithms in the simulations and experiments. Simulation results show that the CVX and homotopy methods can accurately locate in the high molecule density, but the CVX method has the longest running time among these methods. The OMP method has low localization precision in the high density. The experimental results show that these algorithms can realize the localization of high molecule density. The CVX and homotopy methods get better results than OMP method in the localization precision. For the localization of 500 images, the homotopy and OMP methods are 14.9-fold and 21.2-fold faster than CVX method, which can greatly shorten the reconstruction time.