Talk:Deconvolution

message: Some online research (eg his obituary) indicates that A. Lindo Patterson was another colleague of Wiener's involved in the application of the concepts of (de)convolution.  He was working in X-ray crystallography, probably at the same time or earlier than Robinson's work in seismology.  Any information on this topic would be appreciated. This article needs broader information on the history of deconvolution, especially outside of seismology (my own bias). Gwimpey 21:50, 10 April 2006 (UTC)
thread_title: History needs expansion

message: I've seen several references to deconvolution in reference to Nuclear magnetic resonance.  Someone with some knowledge on the topic might want to add a little info. --Tsuji 00:23, 17 August 2006 (UTC)
thread_title:  Deconvolution and NMR 

message: This software is mainly developed for astronomical image processing:
*SImg (GPL'd software)  —Preceding unsigned comment added by 217.114.211.20 (talk) 17:46, 27 January 2008 (UTC)
thread_title:  New software link 

message: Clarkvision_com Saturn Photo Gallery 1
His homepage says:
All images, text and data on this site are copyrighted.
They may not be used except by written permission from Roger N. Clark.
All rights reserved.
- perhaps I shouldn't have copied that - oops!
Do you think it would be worth asking for permission to use his images ? Or at least link there ?
He seems quite an authoritative source IMO - FWIW.
--195.137.93.171 (talk) 02:16, 7 March 2008 (UTC)
thread_title:  Nice example using Richardson-Lucy adaptive restoration 

message: What kind of diagram is required? Please re-add this template with more details about what is wanted. thanks --pfctdayelise (talk) 12:18, 27 July 2008 (UTC)
thread_title: {{tl|reqdiagram}}

message: I'm not an expert in this field, but I think "s(t) = e(t) * w(t)" is incorrect, as it is the functions that are convoluted, not the function values. IMHO the equation should be replaced by "s(t) = e*w(t)" or possibly "s(t) = (e*w)(t)".
Dendropithecus (talk) 18:54, 9 February 2009 (UTC)
thread_title:  Is "s(t) = e(t) * w(t)" correct? 

message: In general if you have a random variable Z that is a sum of two random variables X and Y, the probability density function of the distribution of Z will be the convolution of those of the distributions of X and Y. I have seen references to using deconvolution to estimate the distribution of the components from the distribution of their sum (and presumably either the exact or estimated distribution of the other components, or some assumptions about their nature.) Unfortunately I don't know enough about the subject to write any useful encyclopedic information about it. 200.125.112.113 (talk) 18:35, 16 July 2009 (UTC)
thread_title:  statistics of distributions 

message: Hi folks, I added a link to shareware for image deblurring that I recently released. Hope its ok for you. In other case, please contact me to discuss it. Filip  —Preceding unsigned comment added by 78.45.58.52 (talk) 18:37, 20 December 2009 (UTC)
thread_title:  Shareware added 

message: Deconvolution is used to identify the inverse transfer function of a plant and use the obtained model to drive the plant (to control). See "Adaptive iverse control", Bernard Widrow, 1993. - 81.180.223.197 (talk) 08:18, 9 July 2011 (UTC)
thread_title:  Inverse identification 

message: There is a proposal of merger between blind deconvolution and deconvolution.
I disagree with this. Although the name blind deconvolution suggests that it is merely a special case of deconvolution, it is not. Convolution and deconvolution are well-defined mathematical operations while blind deconvolution is an entirely different story.
First of all, it is not well-defined (there is no "correct answer") hence it does not belong to the field of mathematics, but rather in applied mathematics. Blind deconvolution is subjective while deconvolution is objective.
Secondly, blind deconvolution is an area of active research where progress is still being made (in contrast to convolution/deconvolution which are "just algorithms"). The methods used in blind deconvolution are highly dependent on their underlying applications and there is much to be said about the different methods used.  — Preceding unsigned comment added by 130.238.58.207 (talk) 18:39, 15 October 2013 (UTC)
thread_title:  About merger with blind deconvolution 

message: When in a dark room with a brightly-lit scene outside, if there is an aperture (like a hole in a opaque curtain, or the triangular small gap if the curtains are not completely closed), an inverted and reversed image of the outside scene may be seen as splotches of coloured light on the walls of the dark room.
This is a large-aperture version of the pinhole camera.
It is fuzzy because each point source of light in the outside scene produces its own (e.g.) triangular patch of light on the inner wall - that shape and size is the function g in the above f * g = h (corresponding to the transfer function of an instrument).
A clear image of the outside scene can be recovered from a photograph of this fuzzy image on the internal wall, by deconvolution, using the shape, dimensions and orientation of the hole in the curtains.
{I am 77yo and want another physicist to check this} davd (talk) 18:34, 10 January 2014 (UTC)
replies: text: AIUI the problem with the large pinhole is it's essentially a form of spacial lowpass filter, so when you invert it you end up with very high gain on the components with high spacial frequency and that leads to a noisy reconstruction. 151.229.191.223 (talk) 03:07, 22 June 2014 (UTC)
thread_title:  Example of convolution, seen frequently 

message: It seems to me that the article should separate, and mention the difference between, linear and non-linear deconvolution.   Dividing the Fourier transforms is linear. This is well described in Jansson's Deconvolution of Images and Spectra, Second Edition. It adds the restriction that intensity can't go negative, and often works much better in signals with noise (all of them). Gah4 (talk) 21:52, 6 November 2020 (UTC)
thread_title:  linearity