Analysis and Comparison of Image Enhancement Techniques for Improving PSNR of Liver Images by Median Filtering over Mask Filtering

Abstract

Aim: The goal of this research is to employ median filters and mask filters to reduce noise in liver images so that they can be improved. In addition, the Peak Signal to Noise Ratio of both filters’ outputs was examined (PSNR). Materials and Methods: The afflicted and normal liver photos were obtained from the Kaggle website for this investigation. Then, using Matlab software, the mask filtering and median filtering algorithms were run. Clinicalc. com was used to compute sample size, and SPSS software was used to conduct the comparative analysis. This study has two groups, each with a sample size of 20 people with an average G power of 80%. The innovative median filter’s performance is assessed, and the PSNR performance metric is compared to that of the mask filter. Results: The PSNR of innovative median filters is 64.0310, while mask filters have a PSNR of 78.0095, according to Matlab simulation data. The significant value of PSNR (Peak Signal to Noise Ratio) (0.409) and p>0.05 was found in the statistical analysis. Conclusion: The innovative median filter delivers greater PSNR than the mask filter for medical image enhancement on ultrasound liver pictures, according to this study.