Analysis of effect of cycle spinning on wavelet- and curvelet-based denoising methods on brain CT images

The purpose of this paper is to carry out the assessment of effect of cycle spinning on wavelet- and curvelet-based noise reduction methods on brain CT images. In particular, multiscale curvelet- and wavelet-based denoising methods are evaluated with and without cycle spinning. This assessment is focused not only on the noise suppression but also on fine details preservation. The experimental results show that the cycle spinning-based curvelet method outperforms not only other curvelet- based methods but also the wavelet- based methods. The quality assessment parameters taken in this paper are signal-to-noise ratio (SNR), peak-signal-to-noise ratio (PSNR), universal quality index (UQI), structural similarity index metries (SSIM), and edge keeping index (EKI).