Adaptive Non-local Means Denoising Algorithm for Cone-Beam Computed Tomography Projection Images

Aiming at the difficulty of choosing filtering parameters of Non-Local Means (NLM) denoising algorithm for Cone-Beam Computed Tomography (CBCT) projection images, an adaptive NLM denoising algorithm is proposed. First, a simplified noise estimation method based on sub-block division is proposed to replace the approach of designating the background region, which can adaptively identify the background region and estimate the noise level when the background region is changed obviously. And then an algorithm of adaptively obtaining filter strengths of projection images is proposed by analyzing the impact of filter strength to filtering result in NLM denoising algorithm, in which the filter strength is adjusted according to the characteristics of current image and the noises in all projection images are suppressed to a similar level. The experimental result shows that the proposed algorithm can accurately estimate the noise level of projection image and markedly improve the slice image quality.