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

Abstract

Aim: The purpose of this study is to use median filters and wiener filters to minimize noise in liver images in order to improve them. In addition, the output of both filters was analyzed based on their Peak Signal to Noise Ratio (PSNR). Materials and Methods: The research includes two groups; each group has a sample size of 20. Grayscale medical images collected from the kaggle website were used in this research. Samples were considered as (N=20) for guided filter and (N=20) for fast bilateral filter with total sample size 40 calculated using clinicalc.com. Image enhancement is used to enhance the niceness of a picture for the visible notion of human beings. The kaggle website was used to collect data for this study. According to clinical.com, samples were considered as size 20 for PSNR ratio of image G power of 80%, and total sample size determined. Using matlab programming and a standard data set, the Linear filtering, Median filtering were computed. Results: According to Matlab simulation results, unique median filters have a PSNR of 48.1240, while wiener filters have a PSNR of 67.8360. Comparison of PSNR values are done by independent sample test using IBM-SPSS software. There is a statistical insignificant difference between both techniques. The significant value of PSNR (Peak Signal to Noise Ratio) (0.409) and p>0.05 was found in the statistical analysis. Conclusion: On ultrasound liver pictures, the innovative median filter gives greater PSNR than the wiener filter for medical image enhancing purposes, according to this study.