CT Image Denoising Using Double Density Dual Tree Complex Wavelet with Modified Thresholding
Peng Luo, Xilong Qu, Xie Qing, Jinjie Gu · 2018
Due to low radiation dose and software fault, CT images are noisy. How to extraction of meaningful information from noisy CT images are challenging works. In this work, we present a new denoising algorithm for CT image using double density dual tree complex wavelet transform (DDCWT). Firstly, we use DDCWT decompose noisy CT image into high frequency and low frequency components. In the next, a modified threshold is used for DDCWT coefficient. Finally, the denoised image is obtained by reconstructing high frequency and low frequency components through inverse decomposition of DDCWT. Experimental results demonstrate that the improved DDCWT can maintain more rich details and have a higher practical value.