Wavelet-based Rician noise removal for magnetic resonance imaging
IEEE Transactions on Image Processing
Combined Wavelet and Nonlinear Filtering for MRI Phase Images
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Wavelet-based de-noising techniques in MRI
Computer Methods and Programs in Biomedicine
| Hi-index | 0.00 |
Complex images with low signal to noise ratio (SNR) appear in various applications. To recover the associated phase images, noise effects, as loss of contrast and phase residues that can deteriorate the phase unwrapping process, should be reduced. There are various methods for noise filtering in complex images, however most of them deal only with the magnitude image. Only few works have been devoted to phase image de-noising, despite the existence of important applications like Interferometric Synthetic Aperture Radar (IFSAR), Current Density Imaging (CDI) and Magnetic Resonance Imaging (MRI). In this work, a group of de-noising algorithms in the wavelet domain were applied to the complex image, in order to recover the phase information. The algorithms were applied to simulated and phantom images contaminated by three different noise models, including mixtures of Gaussian and Impulsive noise. Significant improvements in SNR for low initial values (SNR