Classic Maximum Likelihood Estimation

The Classic Maximum Likelihood Estimation (CMLE) is the most general Restoration Method available in the Huygens Software. The iterative Classic Maximum Likelihood Estimation (CMLE) algorithm is a Restoration Method avaliable in the Huygens Software based on the idea of optimizing the likelihood of an estimate of the object given the measured image and the Point Spread Function (PSF). The object estimate is in the form of a regular 3D image. The likelihood in this procedure is computed by a Quality Criterion under the assumption that the Photon Noise is governed by Poisson statistics. For this reason it is optimally suited for low-signal images. In addition, it is well suited for restoring images of point- line- or plane like objects.

It is a Non Linear Iterative Method that allows the recovery of some lost information.

The CMLE method uses a Quality Criterion directly derived from concept of Maximum Likelihood: the I-divergence. It efficiently optimizes the quality criterion, and has the possibility to escape local minima which would lead to a wrong solution.