11 April 1996 Maximum likelihood technique for blind noise estimation
Author Affiliations +
Proceedings Volume 2708, Medical Imaging 1996: Physics of Medical Imaging; (1996); doi: 10.1117/12.237784
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States
We propose a novel technique for estimation of image noise amplitude without a priori signal information. Knowledge of the normalized noise distribution is used to construct an approximate Wiener filter parametrized by the estimated noise amplitude. For a given noise amplitude, the resulting signal estimate is subtracted from the image to produce a sample noise estimate. The estimated noise amplitude is varied in order to maximize the probability that the noise estimate is a sample of the known noise distribution with the estimated variance. Probability is measured by the (chi) 2 distribution. The technique is tested for several images by adding stationary zero-mean Gaussian noise with varying amplitude. The variation of estimated versus added noise variance is very nearly linear with unit slope for all of the images tested. The estimated noise variance for images with no added noise is generally small compared to the signal power unless the signal power spectrum is nearly white.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert A. Close, James Stuart Whiting, "Maximum likelihood technique for blind noise estimation", Proc. SPIE 2708, Medical Imaging 1996: Physics of Medical Imaging, (11 April 1996); doi: 10.1117/12.237784; https://doi.org/10.1117/12.237784

Interference (communication)

Statistical analysis

Image filtering

Image analysis

Filtering (signal processing)

Digital filtering

Error analysis


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