Scientific Volume Imaging b.v.
There are very compute-intensive situations, for example when deconvolving 3D-Time Series, in which faster Restoration Methods can be used. In these cases you may consider to use Quick Maximum Likelihood Estimation (QMLE) which is much faster than the Classic Maximum Likelihood Estimation (CMLE) and will give excellent results as well.
The QMLE is roughly five times more efficient than the CMLE while it takes also slightly less time per iteration. So ten QMLE iterations are equivalent to fifty iterations in CMLE.
While CMLE is superior in handling low Signal To Noise Ratio (SNR) data, like low light level confocal images, it is slower that QMLE. In principle CMLE with a Signal To Noise Ratio > 60 converges to the same result as QMLE gives you, but after many more iterations.
In short for good quality widefield images QMLE is the best choice.
The QMLE is available in Huygens Professional, and in the Batch Processor of the Huygens Essential.
