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  2. Deconvolution - Wikipedia

    en.wikipedia.org/wiki/Deconvolution

    Deconvolution maps to division in the Fourier co-domain. This allows deconvolution to be easily applied with experimental data that are subject to a Fourier transform. An example is NMR spectroscopy where the data are recorded in the time domain, but analyzed in the frequency domain. Division of the time-domain data by an exponential function ...

  3. Wiener deconvolution - Wikipedia

    en.wikipedia.org/wiki/Wiener_deconvolution

    In mathematics, Wiener deconvolution is an application of the Wiener filter to the noise problems inherent in deconvolution. It works in the frequency domain , attempting to minimize the impact of deconvolved noise at frequencies which have a poor signal-to-noise ratio .

  4. Point spread function - Wikipedia

    en.wikipedia.org/wiki/Point_spread_function

    An example of an experimentally derived point spread function from a confocal microscope using a 63x 1.4NA oil objective. It was generated using Huygens Professional deconvolution software. Shown are views in xz, xy, yz and a 3D representation. In microscopy, experimental determination of PSF requires sub-resolution (point-like) radiating sources.

  5. Blind deconvolution - Wikipedia

    en.wikipedia.org/wiki/Blind_deconvolution

    In image processing, blind deconvolution is a deconvolution technique that permits recovery of the target scene from a single or set of "blurred" images in the presence of a poorly determined or unknown point spread function (PSF). [2] Regular linear and non-linear deconvolution techniques utilize a known PSF.

  6. Richardson–Lucy deconvolution - Wikipedia

    en.wikipedia.org/wiki/Richardson–Lucy...

    The Richardson–Lucy algorithm, also known as Lucy–Richardson deconvolution, is an iterative procedure for recovering an underlying image that has been blurred by a known point spread function. It was named after William Richardson and Leon B. Lucy , who described it independently.

  7. Wiener filter - Wikipedia

    en.wikipedia.org/wiki/Wiener_filter

    Let (+) be an unknown signal which must be estimated from a measurement signal (), where is a tunable parameter. > is known as prediction, = is known as filtering, and < is known as smoothing (see Wiener filtering chapter of [1] for more details).

  8. Microscopy - Wikipedia

    en.wikipedia.org/wiki/Microscopy

    Antonie van Leeuwenhoek (1632–1723). The field of microscopy (optical microscopy) dates back to at least the 17th-century.Earlier microscopes, single lens magnifying glasses with limited magnification, date at least as far back as the wide spread use of lenses in eyeglasses in the 13th century [2] but more advanced compound microscopes first appeared in Europe around 1620 [3] [4] The ...

  9. Total internal reflection fluorescence microscope - Wikipedia

    en.wikipedia.org/wiki/Total_internal_reflection...

    The deconvolution technique is simply using an inverse fourier transform to obtain the original fluorescence signal and remove the artifact. [ 19 ] Nevertheless, deconvolution has only been shown to work if there is a strong fluorescence signal or when the noise is clearly identified.