A comparative performance analysis of discrete wavelet transforms for denoising of medical images

Abstract

In general, during image acquisition and transmission, digital images are corrupted by noises due to various effect. The complex type of additive noises disturbs images, depending on the storage and capture devices. These medical imaging devices are not noise free. The medical images used for diagnosis are acquired from Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray Instruments. Reduction of visual quality due to addition of noise complicates the treatment and diagnosis. Removal of additive noise in images can easily be possible using simple threshold methods. In this paper we proposed an algorithm for denoising using Discrete Wavelet Transform (DWT). Numerical results shows the performance (based on parameters like: PSNR, MSE, MAE) of algorithm using various wavelet transforms for different Medical Images corrupted by random noise.