CT Image Denoising Based on Thresholding in Shearlet Domain

Abstract

Computed tomography (CT) is a powerful tool for medical diagnosis. Due to acquisition and transmission in CT imaging, the noise appears that leads to poor image quality. Noise reduction technique is applied in CT images where noise is reduced with preserving all clinical information. In this paper, original noisy CT images are thresholded using bayes shrinkage rule in Shearlet domain. The proposed framework is compared with existing methods and it is observed that performance of proposed method is superior to existing methods in terms of visual quality, Image Quality Index (IQI) and Peak Signal-to-noise Ratio (PSNR).