Enhancing X-ray images using novel Kalman’s filter over median filter for removing noise with improved accuracy

This research presents the work on to improve SNR accuracy using Novel Kalman’s Filter over Median Filter in removing noise from X-ray Images. In the research, the efficacy of two different methods for dropping noise level in x- ray images, namely Novel Kalman’s Filter and Median Filter, was examined. The study involved two groups, Group 1 using Kalman’s Filter and Group 2 using Median Filter. Each group consisted of 20 iterations, resulting in a total of N equals 40 iterations and sample size of 1680 being utilized for the analysis. Using the clincalc website, the population size was determined with an alpha rate of 0.05 and a G-Power of 80%. The "Statistical Package for the Social Sciences (SPSS)" program was used to conduct the statistical study. The suggested approach by using Kalman’s filter over the median filter, noise in x-ray pictures may be eliminated, improving accuracy by 92.31% and 90.80%, respectively. A mean of 92.31%, a standard deviation of 0.24373, and a standard error mean of 0.5450 were obtained using the Kalman’s Filter. The mean, standard deviation, and standard error mean for the median filter are 90.8005%, 0.24842, and 0.5555, respectively. From the multiple trails of the two groups, the outcomes showed a substantial variance between the two algorithms, as indicated by the p-value of 0.002 (p