Multi-Modal Medical Image Denoising using Wavelets: A Comparative Study
Rajesh Patil*
and Surendra BhosaleElectrical Engineering Department, VJTI, Mumbai, India.
Corresponding Author E-mail: rapatil@el.vjti.ac.in
Abstract: In medical image processing Noise removal is an important step for recreating a high-quality image like X-ray, ultrasound, MRI etc. While acquiring, transmitting, and retrieving from storage devices normally images are degraded due to noises like Gaussian, Speckle etc. So, noise must be removed from the images for proper diagnosis. Researchers are still looking for an effective noise reduction means. Wavelet Transform (WT) is considered as a powerful transform method for removal of noise. For denoising of medical images affected by Gaussian noise, various wavelets have been proposed. In this paper, various wavelets are used to study the denoising multi-modal medical images affected by Gaussian noise. Here, proposed wavelet gives better results than the wavelets which have been implemented so far now. Denoising results of medical images are compared on the basis of Root Mean Square Error (RMSE), Signal-Noise Ratio (SNR), Peak Signal-Noise Ratio (PSNR) and execution time (TE).
Keywords: CT – Scan; Medical Image Denoising; MRI; Wavelet Transform (WT); Ultrasound; X-ray Back to TOC