Aim: This work aims at developing an artificial intelligence tool which focuses on enhancing the quality of input images. Edge-preserving filter is used for image smoothing and enhancement in image preprocessing stage. Innovative edge preserving filters such as bilateral filtering and anisotropic diffusion filtering design have been attempted in this work. Materials and Methods: In this research, a bilateral filter for edge preserving in images is proposed and developed for collected images and the proposed work is compared with another innovative edge preserving method called anisotropic diffusion filtering method. Input images (N=20) of both groups were downloaded from standard medical database kaagle.com. The enrolment ratio is obtained as 1 with 95% confidence interval and a threshold value 0.05. Results: The performance of image enhancement is measured using two parameters namely PSNR and SSIM. These parameters are calculated and evaluated to assess the proposed methods efficacy. High values of PSNR and SSIM indicate better edge preserving filtering. Bilateral filtering provides the mean PSNR (p=0.536) value of 20.247 and mean SSIM (p=0.083) value of 0.9441. Anisotropic diffusion filtering provides the mean PSNR value of 30.423 and mean SSIM value of 0.9079. Conclusion: Based on the experiments results from MATLAB software and from independent sample t-test results of IBM-SPSS software, edge preserving filtering using bilateral filtering significantly performed better than the anisotropic diffusion filtering.