Image Denoising using Wavelet based Curvelet Transform

Abstract

In number of biomedical applications the images are analysed to detect different types of diseases like tumour or so. With the help of sensors we obtain the images, but these are usually polluted with different types of noise. Hence the removal of noise from medical images is an important task, particularly in MRI, CT. Therefore noise removal is an important step to be carried out prior to analysis. Choosing a correct type of filter is ademanding task always. Here we suggest a technique to condemn medical images using Wavelet Transform and Curvelet Transform. Merit of Fourier Transform is Wavelet Transform, but it has temporary resolutions. I.e. it captures both frequency and location information, when noise characteristics are complex and critical Curvelet-based approach information is needed. Thus the Wavelet-based Curvelet method is used with the hard thresholding algorithm to clear the noises.