title: A method for local deconvolution.
abstract: A new method for deconvolution of one-dimensional and multidimensional data is suggested. The proposed algorithm is local in the sense that the deconvolved data at a given point depend only on the value of the experimental data and their derivatives at the same point. In a regularized version of the algorithm the deconvolution is constructed iteratively with the help of an approximate deconvolution operator that requires only the low-order derivatives of the data and low-order integral moments of the point-spread function. This algorithm is expected to be particularly useful in applications in which only partial knowledge of the point-spread function is available. We tested and compared the proposed method with some of the popular deconvolution algorithms using simulated data with various levels of noise.
authors.affiliation: CSIRO Manufacturing and Infrastructure Technology, Private Bag 33, Clayton South, Victoria 3169, Australia. tim.gureyev@csiro.au
authors.forename: Timur E
authors.initials: TE
authors.lastname: Gureyev
authors.forename: Yakov I
authors.initials: YI
authors.lastname: Nesterets
authors.forename: Andrew W
authors.initials: AW
authors.lastname: Stevenson
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Wilkins