Denoising in Contrast-Enhanced X-ray Images

In this paper, we propose a denoising and contrast-enhancement method for medical images. The main purpose of medical image improvement is to transform lower contrast data into higher contrast, and to reduce high noise levels. To meet this goal, we propose a noise-level estimation method, whereby the noise level is estimated by computing the standard deviation and variance in a local block. The obtained noise level is then used as an input parameter for the block-matching and 3D filtering (BM3D) algorithm, and the denoising process is then performed. Noise-level estimation step is important because the BM3D algorithm does not perform well without correct noise-level information. Simulation results confirm that the proposed method outperforms other benchmarks with respect to both their objective and visual performances. © 2016, Springer Science+Business Media New York.