Lifting the fog: Image restoration by deconvolution

Deconvolution is a data processing technique that is very widely used in science and engineering. Any microscope image of a fluorescent specimen can, in principle, be deconvolved after acquisition in order to improve contrast and resolution. The most common application in biology is for deblurring images acquired as three-dimensional (3D) image stacks using a wide-field fluorescence microscope, where each image includes considerable out-of-focus light or blur originating from regions of the specimen. Deconvolution and confocal imaging are by no means mutually exclusive. Confocal imaging can nearly always benefit from the improvements in contrast, signal-to-noise ratio, and resolution afforded by restorative deconvolution methods. Deconvolution, particularly the more advanced approaches, is implemented through a software package where the algorithm is generally assisted by data correction before and noise reduction steps both before and between iterations. With a given deconvolution package, the quality of results obtained will depend foremost upon the quality of raw image data and upon the accuracy of PSF data.