All optical imaging systems, which work in atmospheric turbulence, are influenced by refraction index fluctuations that often affect beam’s utility. We present a comparison of four methods (Wiener Filter (WF), Regularized Filter (RF), Lucy-Richardson Method (LRM), Blind Deconvolution Method (BDM)), which are used to improve the quality of an image observed through horizontal-path atmospheric turbulence. We use simulation and real image acquisition in both weak and strong turbulence conditions to assess performance of chosen methods. Simulation is used to generate an image distorted along the horizontal optical path by convolution of turbulence-degraded point spread function (PSF) with original image, the result being restored by these four methods. Additionally, modified von Karman phase power spectrum density (PSD) is used for generation of phase screens to simulate weak and strong Kolmogorov turbulence, with different Fried parameters. Restoration results are compared by MTF (Modulation Transfer Function) on edges, and running time. It is shown that LRM produces the best image quality. For studying how the methods perform in real images, an experiment is carried out to capture the real images against varying turbulence strengths. These turbulence-induced images are restored by the same methods mentioned above. The experimental results are compared by the above criteria with modeling results, this demonstrates that LRM shows the best image quality, with highest MTF values and relatively short processing time.