Unsupervised Wiener-Hunt deconvolution 1.0

udeconv - Unsupervised Wiener-Hunt deconvolution[xEap, gnChain, gxChain] = udeconv(data, ir, reg, criterion, burnin, maxIter)return the deconvolution of 'data' by 'ir' with the 'reg' regularization operator. 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, please add a citation of the reference below.Compatible with octave.PARAMETERSdata -- the datair -- the impulsionnal responsereg -- the regularisation operator (a laplacian for example)criterion -- if the difference between two successive estimate is less than this value, stop the algorithm.burnin -- number of iteration to remove at the beginning of the chain to compute the mean of the image (typicaly 30).maxIter -- maximum number of iteration (typicaly 200).OUTPUTSxEap -- the estimated resultxStd -- is the standart deviation around the estimategnChain, gxChain -- the MCMC chain of the regularisation parameters. See reference below.FUNCTION CALL[xEap gnChain, gxChain] = udeconv(data, ir, hpFilter, criterion, burnin, maxIter)[xEap gnChain, gxChain, xStd] = udeconv(...)REFERENCEFrandoTzois Orieux, Jean-FrandoTzois 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 ://http://www.opticsinfobase.org/josaa...osaa-27-7-1593

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Beginning,  Chain,  Estimate,  Image,  Maximum,  Outputs,  Remove,  Successive,  Typicaly
Users rating:	0/10