Order Statistics Filters in Wavelet Domain for Color Image Processing
MICAI '07 Proceedings of the 2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session
Wavelet-Based methods for improving signal-to-noise ratio in phase images
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Wavelet-based Rician noise removal for magnetic resonance imaging
IEEE Transactions on Image Processing
A Bayesian filtering technique for SAR interferometric phase fields
IEEE Transactions on Image Processing
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Complex images from different processes are often acquired with a low signal to noise ratio, as it is the case with Magnetic Resonance Imaging. Noise filtering is used to recover the associated phase images, mitigating negative effects such as loss of contrast and the introduction of phase residues, which constitute a major drawback for phase unwrapping processes. In this work, a group of algorithms combining nonlinear filters and wavelet de-noising were developed and applied to MRI images, in order to recover the phase information. The results obtained with the two algorithms that exhibited the best performance when applied to both phantom and real images, are shown. Application of these algorithms resulted in improvements both in terms of SNR and of the decrement in the number of phase residues.