Unsupervised Wiener-Hunt deconvolution

Return the Wiener-Hunt deconvolution of data without tuning parameters.

udeconv - Unsupervised Wiener-Hunt deconvolution

xEap = udeconv(data, ir, ...)
[xEap, gnChain, gxChain] = udeconv(data, ir, ...)

return the deconvolution of 'data' by 'ir'. The algorithm is a stochastic iterative process (Gibbs sampler) that allow automatic tuning of regularization parameter, see reference below. There is no specific constraints on the number of dimension.

The call [xEap, gnChain, gxChain, xStd] = udeconv(...) allow to compute the diagonal of the covariance matrix around xEap with the cost of an fft at each iteration.

If you use this work, add a citation of the reference below.

Compatible with octave.

PARAMETERS

data -- the data

ir -- the impulsionnal response

OPTIONNALS

Optionnals argument are in the form (..., 'key', val, ...).

'criterion', val -- if the difference between two successive estimate is less than this value, stop the algorithm. Default is 1e-4.

'burnin', val -- number of iteration to remove at the beginning of the chain to compute the mean of the image. Default is typicaly 30.

'maxIter', val -- maximum number of iteration. Default is 150.

OUTPUTS

xEap -- the estimated result

gnChain, gxChain -- the MCMC chain of the regularisation parameters. See reference below.

xStd -- is the standart deviation around the estimate

FUNCTION CALL

xEap = udeconv(data, ir)

[xEap gnChain, gxChain] = udeconv(...)

[xEap gnChain, gxChain, xStd] = udeconv(...)

REFERENCE

François Orieux, Jean-François Giovannelli, and Thomas Rodet, "Bayesian estimation of regularization and point spread function parameters for Wiener-Hunt deconvolution," J. Opt. Soc. Am. A 27, 1593-1607 (2010)

http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-27-7-1593