Unavoidable noise appears within all the data. Noise and unwanted information mask the true quality of the data. The most crucial element of every shadowgraph which is also known as a dental radiograph, that is crucial for evaluation is quality. Denoising of photos is required to be done for that. Gaussian, median, and mode filters are only a few examples of filters. Quality assessment is necessary in order to verify the uniqueness of dental shadowgraphs. To determine the image quality, an estimate of the ground validity is required. Particularly in dentistry, image denoising is the first step prior to segmentation and classification. To assess the quality of the image, different performance metrics are used namely Peak Signal-to-Noise Ratio, Signal-to-Noise Ratio and Mean Squared Error. For different noises, different filters yield good results in the experimentation. In this work, during noise removal, the Mode, Median and Gaussian filters give better accuracy for Poisson, Salt and pepper & Gaussian, and Speckle noise, respectively.