Spatially Adaptive Non-Gaussian Imaging Via Fitted Local Likelihood Technique
for MATLAB version 6.5 or later
The MATLAB routine Fitted Local Likelihood (FLL) implements
a new technique for spatially adaptive filtering. This statistics is proposed
for selection of an adaptive size estimation neighborhood and based on the
local maximum likelihood estimation. The algorithm is
developed for quite general observation models subject to the class of the
exponential distributions. This algorithm shows a better performance than the
intersection of confidence interval (ICI) algorithm, in particular, for
Poissonian data.
In many applications the noise that corrupts the signal is non-Gaussian and
signal-dependent.
There is a variaty of heuristic adaptive-neighborhood approaches for filtering signal and images corrupted by signal-dependent noise.
The procedure is given for observations subject to the class of exponential
distributions which includes the Poissonian model as an important special case.
The performance of the algorithm is illustrated for image
denoising with data having Poissonian, Gaussian and Bernoulli observations.
The provided demo is open-source, and may be modified and tuned to be exploited with other data.
This DemoBox is available free-of-charge for educational and non-profit scientific research,
enabling others researchers to understand and reproduce our work. Any unauthorized use of the LASIP
routines for industrial or profit-oriented activities is expressively prohibited.
The main routine provided in this DemoBox is the following:
demo_FittedLocalLikelihoodDenoising.m
This demo performs denoising based on the novel statistical multiple
hypothesis testing rule. The data observed is considered to be corrupted with
Gaussian and non-Gaussian (signal-dependent) types of noise. The
Poissonian model of noise is of great importance.
The technique incorporates the
signal-adaptive FLL denoising.
Any unauthorized use of the LASIP routines for industrial or profit-oriented activities is expressively prohibited.
By downloading any of the LASIP files, you implicitly agree to all the terms of the LASIP limited license.
Katkovnik V., and V. Spokoiny,
“Spatially Adaptive Non-Gaussian Imaging via Fitted Local Likelihood Technique.”,
Proc. Int. TICSP Workshop Spectral Meth. Multirate Signal Process., SMMSP 2006,
Florence, 2006.
