Publication

Autofocus for Digital Fresnel Holograms by Use of a Fresnelet-Sparsity Criterion

Michaël Unser, Michael Stefan Daniel Liebling
2004
Journal Articles

Abstract

We propose a robust autofocus method for reconstructing digital Fresnel holograms. The numerical reconstruction involves simulating the propagation of a complex wave front to the appropriate distance. Since the latter value is difficult to determine manually, it is desirable to rely on an automatic procedure for finding the optimal distance to achieve high-quality reconstructions. Our algorithm maximizes a sharpness metric related to the sparsity of the signal's expansion in distance-dependent waveletlike Fresnelet bases. We show results from simulations and experimental situations that confirm its applicability.

Official source

https://infoscience.epfl.ch/entities/publication/4965818e-dd78-47c2-89e3-f851cfcda666

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Michaël Unser, Michael Stefan Daniel Liebling
2004
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4965818e-dd78-47c2-89e3-f851cfcda666

About this result

Related concepts (19)

Levenshtein distance

In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.

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Holography is a technique that enables a wavefront to be recorded and later re-constructed. Holography is best known as a method of generating real , but it also has a wide range of other applications. In principle, it is possible to make a hologram for any type of wave. A hologram is made by superimposing a second wavefront (normally called the reference beam) on the wavefront of interest, thereby generating an interference pattern which is recorded on a physical medium.

Edit distance

In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other. Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question.

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Autofocus for Digital Fresnel Holograms by Use of a Fresnelet-Sparsity Criterion

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