•	Introduction
•	The point spread function
•	Deconvolution by adaptive inverse modelling - the TILLvisDECO approach
•	Requirements for optimal processing of image data in deconvolution experiments
•	Equipment needed for high quality deconvolution results
•	References

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Deconvolution and TILLvisDECO package

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The point spread function

An object and its image are related to one another by a convolution of every point within it. That is to say, every point in the object is replaced by an appropriately blurred point, with the final image represented as the sum of these. The way in which each of these points is convolved can be described by the so-called point spread function (PSF), which is the image of a single point. The PSF is specific for a given set of conditions that include, for example, wavelength, objective NA, and system specific aberrations. Thus, the way in which a microscope images a single, sub-resolution object (such as a fluorescent bead) can be used to define a mathematical convolution relationship between object and image.