Magnetic resonance images denoising using a wavelet solution to laplace equation associated with a new variational model

作者：

Highlights：

• In this paper, we have proposed a new solution to the Laplace equation in terms of the Poisson wavelet transform by changing the initial conditions.

• We have applied this solution to denoise MR images fromthe brain web dataset corrupted by Rician, Rayleigh and white Gaussian noise.

• The denoised images are again denoised by our proposed variational model in order to get better denoised images.

• The performance of the proposed method is compared with some of the other state of the art methods in terms of SSIM values, MSE values and PSNR values.

摘要

•In this paper, we have proposed a new solution to the Laplace equation in terms of the Poisson wavelet transform by changing the initial conditions.•We have applied this solution to denoise MR images fromthe brain web dataset corrupted by Rician, Rayleigh and white Gaussian noise.•The denoised images are again denoised by our proposed variational model in order to get better denoised images.•The performance of the proposed method is compared with some of the other state of the art methods in terms of SSIM values, MSE values and PSNR values.

论文关键词：Initial conditions,Wavelets,Laplace equation,Variational model,Denoising

论文评审过程：Received 10 January 2019, Revised 16 September 2020, Accepted 8 February 2021, Available online 25 February 2021, Version of Record 25 February 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126083