High-ranking noise components are problematic for medical imaging. Medical pictures can be obtained in many ways, including ultrasound, computed tomography, X-ray, and magnetic resonance imaging (MRI). When these processes occur, noise is introduced, lowering the image quality and hampering image interpretation. Images may be cleaned of noise or distortion while keeping their original quality using denoising algorithms. This research investigates the Mean, Median, Gaussian, Canny edge Detection, Wiener, Bilateral, and Laplacian filters on noisy pictures. Random noise and Gaussian noise may both be seen in the image. The Mean Squared Error (MSE), PSNR, and RMS are used to compare the results.

COVID-19, X-ray, RTPCR, AI, CNN, VGG19.