It is well known that magnetic resonance magnitude image data obey a Rician
distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dep
endent, 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-depend
ent bias to the data that reduces image contrast. This paper studies wavele
t-domain filtering methods for Rician noise removal. We present a novel wav
elet-domain filter that adapts to variations in both the signal and the noi
se.