Improved restoration from multiple images of a single object: application to fluorescence microscopy.

We present an approach for the combined restoration of multiple different images of a single object. A linear Tikhonov filter adapted for this purpose is derived in detail. Nonlinear constrained algorithms can also be adapted, and we illustrate this possibility for an iterative constrained Tikhonov algorithm. Both the linear and the iterative constrained Tikhonov algorithms were used to analyze performance in fluorescence confocal imaging by use of simulated and experimental data. One can improve the quality of restored confocal images significantly if the signal that normally is rejected by the detection pinhole of a confocal laser scanning microscope is also recorded on a separate detector such that the two recorded signals are used together for image restoration according to the proposed algorithms.