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https://tcspc.com/lib/exe/fetch.php/logo.pngtext/html2013-08-06T14:41:19+00:00Anonymous (anonymous@undisclosed.example.com)deconvolution
https://tcspc.com/doku.php/glossary:deconvolution?rev=1375800079&do=diff
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<tr><td class="diff-lineheader"> </td><td class="diff-context">====== Deconvolution ======</td><td class="diff-lineheader"> </td><td class="diff-context">====== Deconvolution ======</td></tr>
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<tr><td class="diff-lineheader">-</td><td class="diff-deletedline">===== What is "Deconvolution"? =====</td><td colspan="2"> </td></tr>
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<tr><td class="diff-lineheader"> </td><td class="diff-context">Deconvolution is used in time domain data analysis for removal of broadening effects due to instrumental resolution. In this context deconvolution is mainly concerned with the [[IRF]] (or lamp function) including the finite light source pulse width and other broadening effects (e.g. electronics). The effects caused by the [[IRF]] are dominant in the onset of a decay curve.</td><td class="diff-lineheader"> </td><td class="diff-context">Deconvolution is used in time domain data analysis for removal of broadening effects due to instrumental resolution. In this context deconvolution is mainly concerned with the [[IRF]] (or lamp function) including the finite light source pulse width and other broadening effects (e.g. electronics). The effects caused by the [[IRF]] are dominant in the onset of a decay curve.</td></tr>
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<tr><td class="diff-lineheader"> </td><td class="diff-context">===== How deconvolution should be done =====</td><td class="diff-lineheader"> </td><td class="diff-context">===== How deconvolution should be done =====</td></tr>
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<tr><td class="diff-lineheader">-</td><td class="diff-deletedline">Best, not at all ;-). At <strong class="diff-mark">PQ we use [[reconvolution]] instead</strong>, for a variety of good reasons (see [[IRF]]). If one cannot resist applying deconvolution, the best way of doing it (at least for time domain data) would be via Fourier transform. Fourier transform is a slow process (even with [[FFT]]) and it has to be done twice, since the deconvoultion itself is performed on the transformed data set, which has to be retransformed afterwards.</td><td class="diff-lineheader">+</td><td class="diff-addedline">Best, not at all ;-). At <strong class="diff-mark">PicoQuant</strong>, for a variety of good reasons (see [[IRF]]) <strong class="diff-mark">we use [[reconvolution]] instead</strong>. If one cannot resist applying deconvolution, the best way of doing it (at least for time domain data) would be via Fourier transform. Fourier transform is a slow process (even with [[FFT]]) and it has to be done twice, since the deconvoultion itself is performed on the transformed data set, which has to be retransformed afterwards.</td></tr>
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<tr><td class="diff-lineheader"> </td><td class="diff-context">The most prominent application of deconvolution techniques is imaging. Usually one tries to remove blurring by deconvolution (or deconvolution-like) techniques. What holds for time domain data, also holds for imaging: Deconvolution has a disturbingly high potential for producing artefacts - and there is no way of telling apart artefacts and effects. The images may look nicer (which undoubtedly is valuable especially for publication purposes), but the content of information has not necessarily improved.</td><td class="diff-lineheader"> </td><td class="diff-context">The most prominent application of deconvolution techniques is imaging. Usually one tries to remove blurring by deconvolution (or deconvolution-like) techniques. What holds for time domain data, also holds for imaging: Deconvolution has a disturbingly high potential for producing artefacts - and there is no way of telling apart artefacts and effects. The images may look nicer (which undoubtedly is valuable especially for publication purposes), but the content of information has not necessarily improved.</td></tr>
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</table>text/html2015-02-10T16:35:00+00:00Anonymous (anonymous@undisclosed.example.com)reconvolution
https://tcspc.com/doku.php/glossary:reconvolution?rev=1423586100&do=diff
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<tr><td class="diff-lineheader"> </td><td class="diff-context">Reconvolution is used in time domain data analysis for removal of broadening effects due to instrumental resolution. In contrast to [[deconvolution]], data processing using reconvolution techniques does not aim at retrieving the raw data as seen by an ideal instrument, but does usually compare artificial decays (simulated on the base of a model) convolved with the measured [[IRF]].</td><td class="diff-lineheader"> </td><td class="diff-context">Reconvolution is used in time domain data analysis for removal of broadening effects due to instrumental resolution. In contrast to [[deconvolution]], data processing using reconvolution techniques does not aim at retrieving the raw data as seen by an ideal instrument, but does usually compare artificial decays (simulated on the base of a model) convolved with the measured [[IRF]].</td></tr>
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<tr><td class="diff-lineheader">-</td><td class="diff-deletedline">Reconvolution is used in PicoQuant software packages (mainly [[<strong class="diff-mark">products</strong>:FluoFit]] and [[<strong class="diff-mark">products</strong>:SymPhoTime]]) for compensating IRF effects. </td><td class="diff-lineheader">+</td><td class="diff-addedline">Reconvolution is used in PicoQuant software packages (mainly [[<strong class="diff-mark">software</strong>:FluoFit]] and [[<strong class="diff-mark">software</strong>:SymPhoTime]]) for compensating IRF effects. </td></tr>
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