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| Estimation of Spatially Variable Level Field of Rician Noise and its Application to MR Image Denoising |
1 School of Biomedical Engineering, Southern Medical University, Guangzhou 510515,China
2 Shenzhen Entryexit Inspection and Quarantine Industrial Detection Technology Center, Shenzhen 518067, China |
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Abstract The levels of Rician noise in MR images vary spatially. A method to estimate the noise level field (NLF) was proposed in this paper for denoising the spatially variable noise. The NLF was fitted using the estimations of local noise levels and a NLF model with the sparsity constraint. Then, the noisy MR images were made to be homoscedastic by the spatially adaptive variancestabilization transformations with the estimated NLF. Thus, BM3D algorithm was adopted to suppress the noise in the transformed images. Experimental results on the synthetic and real images demonstrate that the proposed method effectively estimates the NLF and the estimated NLF is useful for denoising the spatially variable Rician noise. The mean relative error of the estimated noise levels was less than 0.2%. Compared with other denoising methods for MR images, the method with NLF performed better and PSNR was improve about 2 dB. The results demonstrate that the proposed method can effectively estimate the Rician noise level field and can be used to suppress the spatially variable Rician noise.
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