Deconvolution algorithm

From HRM 3.7 onwards it is possible to select one deconvolution algorithm per image channel. In most cases this will not be necessary and the user will likely find it convenient to deconvolve all the image channels with the same deconvolution algorithm.

For each channel choose one of the deconvolution algorithms from the corresponding drop down widget.

The available choices are:

• Classic Maximum Likelihood Estimation (CMLE): CMLE is the method of choice under most circumstances. In case of doubt, CMLE should be used.
• Quick Maximum Likelihood Estimation (QMLE): QMLE is faster than CMLE, but gives slightly less precise solutions in some cases. One may consider using QMLE in compute-intensive situations, for example, when deconvolving widefield 3D-time series.
• Good’s roughness Maximum Likelihood Estimation (GMLE): GMLE is a good alternative for high-noise images, such as STED or confocal.
• Skip : for not deconvolving this channel and keeping the raw data instead.

Note

Skip all channels of an image to use HRM as a pure batch file converter, chromatic aberration corrector, time stabilizer, colocalization analyzer, etc.