One of the most important tasks in video processing is denoising, which is the process of improving image quality by reducing noise, especially for high-fidelity applications. The work presents the parallelized scheme of the Fast Non-local Means (FNLM) algorithm, efficient in video denoising and enabling real-time processing of high-resolution videos. Classic FNLM, though very effective in noise reduction, is computationally intensive since it requires thousands of comparisons in the search window for every pixel in an image; this makes the algorithm unsuitable for real-time applications. The method will take full advantage of Message Passing Interface (MPI) in distributed processing. In addition, this will significantly reduce the computational cost without affecting the quality of denoising. MPI spreads frames across multiple nodes, independently doing the denoise on each node and thus balancing the load for minimizing overall processing time. Improved speedups obtained on parallelizing the algorithm against to sequential implementations are demonstrated by experimental findings, confirming that this method is suitable for use in real-world applications involving the denoising of high-definition, real-time videos using the FNLM.