Analysis and Comparison of Wavelet Transforms for Denoising MRI Image

Sugandha Agarwal ¹, O.P. Singh¹ and Deepak Nagaria²

¹Amity School of Engineering and Technology, Amity University, Lucknow.

²Electronics and Communication Department, BIET, Jhansi.

Corresponding Author E-mail: sugandhaa7@gmail.com

Abstract: Medical imaging plays a dominant role in clinical practice like diagnosis, therapy, etc. and research related findings. Medical images are usually contaminated or distorted while acquiring and transmitting the image due to several types of noises, misfocus of camera, disturbance due to blood flow, atmospheric turbulence. So it becomes necessary to apply image denoising processing to improve the quality of image. The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. This paper compares the efficiency of wavelet based thresholding techniques in the presence of speckle noise for various wavelet family i.e. Haar, Morlet, Symlet, Daubechies in denoising a medical imaging resonance of brain. Performance estimation and analysis is done using SNR (Signal to Noise Ratio), PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error). Based on the performance evaluation, it is inferred that wavelet transform is more effective as it has an ability to capture the energy of a signal in a few energy transform values usually known as wavelet coefficients.

Keywords: Image denoising; Threshold; Wavelet transform; MRI; PSNR; and MSE

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