An algorithmic process to reverse the effects of a convolution, which is a linear form of signal or image filtering.
Deconvolution is the process of estimating an original signal (or image) from recorded data. Usually, the process of recording the signal involves a transfer function (in imaging, a point spread function), which is convolved with the original signal and blurs it. Deconvolution can then be applied to improve the signal quality. For example, in fluorescence microscopy deconvolution can be used together with special illumination configurations to obtain super-resolved images. If the transfer function cannot be measured, bind deconvolution can be used to estimate both the original signal and the transfer function simultaneously.
Deconvolution typically involves regularization and iterative optimization methods.
