Talk:Aliasing

message: I added this section as a further example that the conventional wisdom of sinc filters isn't always true. Sinc filtering the measured image g, regardless which sinc filter is used, does not lead to any accurate measurement of the radius of the star.
:I am concerned about this part -- it looks like a description of speckle imaging but has some fundamental misunderstandings (see astronomical seeing for how short exposures of a star really look through the atmosphere). Star diameters are commonly measured in astronomy, but never like this. Unless people complain, I will remove this example, and replace it with a description of how star diameters are measured using speckle interferometry.
Rnt20 06:37, 11 April 2006 (UTC)
thread_title:  An example in astronomy 

message: In my experience, this also happens when watching a spoked wheel. Can someone confirm? (or is this  maybe evidence that I'm living in the Matrix... hm, my head hurts now ;-) -- Tarquin 15:26 Dec 20, 2002 (UTC)
This could be the case if your eye samples the scene - perhaps periferal vision does this. I sometimes get a related effect if I see a TV screen or other flickering source out of the corner of my eye - the flicker frequency appears to be much less than 50Hz. -- Easter 15:32 Dec 20, 2002 (UTC)
For really freaky effects, try watching a TV screen or CRT monitor while using an electric toothbrush. The image wobbles up and down, it was quite alarming the first time I saw it. -- Tarquin
This is what my colleagues in broadcast engineering call the ginger biscuit effect. Any vibration to the head will do.  -- Easter 15:47 Dec 20, 2002 (UTC)
I think we need an article on this! -- Tarquin
This effect is caused by a failure of persistence of vision, although it could also be regarded as a kind of aliasing (with the vibration of your head providing the sampling frequency).  I don't believe that the eye normally does any sampling in the time domain, at least not in a periodic way.  Devices like CRT monitors rely on your persistence of vision, which is the slow response of your retina to changing or flickering images.  This only works if your eye muscles can produce a stationary image on the retina.  When you move your head faster than your eye muscles can track, as happens when you eat crunchy food, the TV image is spread out over your retina and appears fragmented, because parts of your retina see one field of the image and other parts see the next field, or the few milliseconds of darkness between fields.  I'm guessing that this effect is more noticeable at the edge of the field of view, because the mechanism that stabilises the eyeball mainly uses data from the centre of the retina. -- Heron 11:30, 31 Mar 2004 (UTC)
replies: text: There's an exhibit at the Exploratorium that makes use of this phenomenon: Bronx Cheer Bulb. - mako 05:02, 15 October 2005 (UTC)
replies: text:  With regards to the electric toothbrush and the TV, I've also noticed it happen when using a vibrating neck messenger BUT it also happens when looking at the reflection of the TV/monitor in the vibrating surface.
Maybe this isn't exactly the same effect, but the most compelling example of this kind of phenomenon I have ever seen occurs when in a dark room, viewing one of those old digital alarm clocks with the red numbering (search for "digital alarm clock" in google images - first few examples are what I'm talking about) just off center, and moving your head around quickly... not violently fast, but fairly fast.  The image of the numbers will appear to not be able to keep up with the physical clock, and drift off it to the left and right, up and down, pretty fair distances if you do it just right.  —Preceding unsigned comment added by 66.31.7.121 (talk) 02:51, 3 February 2008 (UTC)

text: I think the "break up" mentioned in the multiplexed display article is the same as the the Frito Effect under yet another name. --DavidCary (talk) 05:25, 16 June 2013 (UTC)
thread_title: "Filming a spoked wheel"

message: WHAT THE HELL HAPPENED? Loisel 17:55, 29 Jul 2003 (UTC)
replies: text: If you mean the table of contents, see Wikipedia:Software updates. You can turn it off via your preferences if you don't like it. If you mean something else, you're going to have to say what. --Camembert
What's this 4LIQ9nXtiYFPCSfitVwDw7EYwQlL4GeeQ7qSO business? Evercat 17:59, 29 Jul 2003 (UTC)

text: These are unique hashes generated by Tomasz' math functions to identify the contents of a math element. I don't know why they appear when you just type "<math>" though. Ask User:Taw.—Eloquence 18:08, 29 Jul 2003 (UTC)
thread_title: Wikipedia bug (math in headers?)

message: What we need is ONE simple picture showing a sinusoid being sampled at too high rate and matching a lower-frequency sinusoid. Then we can probably delete some 10,000 words... Jorge Stolfi 20:46, 23 Mar 2004 (UTC)
replies: text: Added such a picture.Jorge Stolfi 22:16, 23 Mar 2004 (UTC)
thread_title: Picture of aliasing

message: The sound example needs more explanation: what is the sampling rate, what exactly is meant by "bandlimited", and what should the listener pay attention to. Jorge Stolfi 18:43, 24 Mar 2004 (UTC)
thread_title: Sound example

message: Having specifically said that the Nyquist condition is simplistic, I don't think the following theory adequately explains why this is the case.  I mean, it may explain it, but it doesn't specifically summarize why it is that the Nyquist criterion is therefore simplistic.  I don't think readers should have to dig so much, only to find vague statements under caveats -- Tlotoxl 10:15, 31 Mar 2004 (UTC)
replies: text: I added something at the end. Do you like it? Loisel 07:24, 8 Apr 2004 (UTC)
thread_title: The Nyquist criterion is in fact simplistic...see below

message: Shouldn't there be a mention about aliasing in TV broadcast? The reason why moderators don't have certain patterns of dress and so on. Just a thought. 84.42.132.48 11:31, 1 September 2005 (UTC)
thread_title:  aliasing on TV 

message: Right at the start of the article, where it says:
: Aliasing is a major concern in the digital-to-analog conversion of video and audio signals: improper sampling of the analog signal will cause high-frequency components to be aliased with genuine low-frequency ones, and be incorrectly reconstructed as such. To prevent this problem, the signals must be appropriately filtered, before sampling.
shouldn't that be analog-to-digital not digital-to-analog or am I just confused?
This paragraph seems to by trying to say that aliasing occurs when you sample analog to digital. It says improper sampling of the analog signal will cause... That seems to imply that analog is the source in this paragraph.
It seems confusing as written, someone who knows better please help me understand this. HighInBC 18:12, 27 February 2006 (UTC)
replies: text: You're right. I fixed it. --Heron 19:56, 27 February 2006 (UTC)
thread_title:  digital-to-analog?? 

message: Can someone explain the new animated example.  It seems way too busy and confusing.  Do we really need animation for this?  Can it be explained with some commentary at least?  I'm going to take it out for now.  Please comment if you like it, or put it back with commentary, or make a more accessible example. Dicklyon 02:44, 4 July 2006 (UTC)
replies: text: "A" for effort, but I don't think it's ready for Wikipedia (and vice-versa).  Maybe there is an article on animated gif images.  If not, better yet... let's start one.  --Bob K 07:36, 4 July 2006 (UTC)
thread_title: Animated example

message: Apparently I've made no progress getting Rbj to understand the notion of mathematical implication, and the difference between a provably true theorem and its not-always-true converse.  He has come over here to spread his joy, having "crapped up" (his words) the Nyquist–Shannon sampling theorem article in the last day or two.  He has a narrow view of aliasing based on baseband reconstruction, which he is also mixing up with the notion of an alias itself.  My changes are individually documented to indicate the errors in what he has done. Dicklyon 15:43, 17 August 2006 (UTC)
thread_title: Rbj's false converse assertions

message: I don't thing there's a lot of point having a separate article for this that contains three sentences, all of which are already implied by the content of this article.  Any reason not to just redirect it to here and remove the link from this article? JulesH 09:56, 21 November 2006 (UTC)
replies: text: Sure enough, top several GBS hits on "spatial aliasing" are in seismology and magnetotellurics books:  .  Anyone feel qualified to add a bit about that? Dicklyon 20:06, 21 November 2006 (UTC)

text: So are you going to write it?  Is there not room in this article for what you want to add? Dicklyon 04:22, 2 December 2006 (UTC)
thread_title:  merge from spatial aliasing 

message: The POV "ancillary comment" about that linked PDF sounds like something I may have written in my early wikipedia days; if so, it sure lasted a long time, but you're right it sure doesn't belong.  Anyway, specific complaints about the Lavry PDF include:
* Starts with false statment "Dr. Nyquist discovered the sampling theorem".
* It refers to the sampling theorem as a "theory".
* It's a diatribe in the sense that "the author's motivation is to help dispel the wide spread misconceptions regarding sampling of audio at a rate of 192KHz" and yet in tons of pages he fails to make a convincing case or to support his conclusions that are basically just opinions.
* His topic has only a tangential relationship to the sampling theorem and little relationship to the aliasing article.
So, now that the disclaimer is gone, I think I'll remove the ext link, too.  Dicklyon 21:38, 22 January 2007 (UTC)
thread_title: Ext link to Lavry's "diatribe"

message: In section 5.1, we have:
:For the purposes of this analysis, we define a continuous-time signal as a real or complex valued function whose domain is the interval [0,1]. 
In section 5.6, we conclude with:
::S_\mathrm{opt}g=S_0(\mathrm{sinc}*g) \ 
:where \mathrm{sinc}*g \  is some sort of sinc filter or sinc function.
In case it isn't obvious, I think what we are saying is that an anti-aliasing filter (and a rectangular one at that) is a good thing to do before sampling.
But how do we confine a sinc function to the interval [0,1]?  Is that why we need the "some sort of" caveat?  And how do we design a "sort of sinc" filter?
Frankly, these sections don't do much for me.  Why "teach" functional analysis here?
The relevant points seem to be these:
*A mapping from an higher dimensional space to a lower one loses information that cannot be recovered.
*Filtered sampling is more realistic than instantaneous sampling.
*Filtered sampling is "better" than instantaneous sampling, from the viewpoint of aliasing.
**(assumes the distortion caused by the filter does not count)
*An anti-aliasing filter with instantaneous sampling is equivalent to filtered sampling.
*"Some sort of sinc" filter is the optimum anti-aliasing filter.
Am I missing something?  Are these unsurprising (and in some cases vague) points enough to justify section 5?
--Bob K 14:18, 10 March 2007 (UTC)
replies: text: I agree.  This essay on filtering and sampling is out of place in this article, and is not very logical constructed.  I haven't looked around to see if such material is already covered well in sampling or some such place.  I'm OK with cutting it out. Dicklyon 15:44, 10 March 2007 (UTC)
thread_title:  Sections 5.1-5.6 (Function approximation theory) 

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thread_title:  External links modified