Wavelet-based Rician noise removal for magnetic resonance imaging.
It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dependent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to-noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data that reduces image contrast. This paper studies wavelet-domain filtering methods for Rician noise removal. We present a novel wavelet-domain filter that adapts to variations in both the signal and the noise.
Nowak
R D
RD
Dept. of Electr. and Comput. Eng., Rice Univ., Houston, TX 77251-1892, USA. nowak@egr.msu.edu