Edge Detection Based Medical Denoising using Wavelet Domain

Abstract

In the present scenario, the entire world is doing a lot of investments in the field of medical terminology and to achieve advancement in the medical field. Updated resources and adaptability of new technology in the medical field is the key factor the entire world is looking for. Today, undoubtedly Medical Denoising has become a popular research topic, with new studies being published daily. Thus, denoising of images in medical field images has now turned out to be an important research topic for researchers. In the medical field, CT scanning is an important and commonly preferred technique. In this experiment, edge detection based on medical denoising is performed using two different edge detection operators. For image accession, multiple Computed Tomography CT images are taken from the internet and the entire experiment is carried out on those images. The identification is performed using the Canny operator and Sobel operator and further wavelet domain is implemented on those images that are generated by the above-mentioned edge operators. Further, the performance of the selected operators is evaluated using Structure Similarity Index (SSIM), Peak Signal to Noise Ratio (PSNR), and Mean Absolute Error (MAE), of the image. After the successful completion of the experiment, it was found that both the operators produce different forms of output and work completely differently from one other.