PYME.Deconv.richardsonLucy module

class PYME.Deconv.richardsonLucy.RichardsonLucyDeconvolution

Bases: object

Deconvolution class, implementing a variant of the Richardson-Lucy algorithm.

Derived classed should additionally define the following methods: AFunc - the forward mapping (computes Af) AHFunc - conjugate transpose of forward mapping (computes ar{A}^T f) LFunc - the likelihood function LHFunc - conj. transpose of likelihood function

see dec_conv for an implementation of conventional image deconvolution with a measured, spatially invariant PSF

deconv(data, lamb, num_iters=10, weights=1, bg=0)

This is what you actually call to do the deconvolution. parameters are:

data - the raw data lamb - the regularisation parameter (ignored - kept for compatibility with ICTM) num_iters - number of iterations (note that the convergence is fast when

compared to many algorithms - e.g Richardson-Lucy - and the default of 10 will usually already give a reasonable result)

deconvp(args)

convenience function for deconvolving in parallel using processing.Pool.map

startGuess(data)

starting guess for deconvolution - can be overridden in derived classes but the data itself is usually a pretty good guess.

class PYME.Deconv.richardsonLucy.dec_conv(*args, **kwargs)

Bases: RichardsonLucyDeconvolution, ClassicMappingFFTW

class PYME.Deconv.richardsonLucy.dec_conv_slow(*args, **kwargs)

Bases: RichardsonLucyDeconvolution, ClassicMappingNP

class PYME.Deconv.richardsonLucy.rlbead(*args, **kwargs)

Bases: RichardsonLucyDeconvolution, SpatialConvolutionMapping