Iterative Constrained Tikhonov-Miller (ICTM) estimation

For fluorescence and from a theoretical viewpoint Maximum Likelihood Estimation (MLE) Restoration Methods are the best choices. However, for high Signal To Noise Ratios (SNR) as in widefield images this becomes rather academic. The ICTM method in the Huygens Professional is computationally more efficient than the Classic MLE (CMLE) algorithm, but in most cases the Quick-MLE (QMLE) method is found to be still faster. Since QMLE is also good at handling high SNR widefield images, QMLE has superceded ICTM. For this reason the ICTM menu entry is now located under menu 'Restoration->Legacy->Iterative Tikhonov-Miller' in the Operations window.

As to the 'quality' of the result, that is either a subjective criterion based on visual inspection (ICTM might win in low noise cases) or it is based on a mathematically sound criterion in which case MLE is proven to be best choice. For noisy images like most confocal ones, MLE is not only scientifically more correct, it also produces visually more pleasing images: far less background noise artifacts than ICTM. Furthermore, the MLE algorithm handles noisy backgrounds much better than the ICTM.

For further information, see also the FAQ MLE vs ICTM - Which method is more effective under certain circumstances?.

For a general overview of all algorithms in Huygens see Deconvolution Algorithms.

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