Talk:Spatial anti-aliasing

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Request for article[edit]

This needs a proper article about anti-aliasing with sampling theory etc. Unfortunately I haven't got time at the moment.


We also need to establish in the opening of the article that anti-a only applies to computer displays and printouts -- digital stuff. "real" typaces don't need it. -- Tarquin

Improving the article[edit]

Anti-aliasing is far more general than discussed here: the general outline is:

  • sampling wraps high frequencies into low
  • therefore high frequencies should be removed before sampling
  • a low-pass filter used for this purpose is called an anti-aliasing filter
  • (make mention of reconstruction filters on the reconstruction side of the system)
  • applies to digital imaging, digital audio, etc. etc.

-- Anon.

I dispute this engineer-centric recommendation. "Wrapping high frequencies into low" isn't a very accurate description at best, and simply misleading at worst. Aliasing is based on the pigeonhole principle, and the sinc/signal processing based approaches comes from blind faith in the Fourier transform. Don't take me wrong, I'm a mathematician with some specialization in the Fourier transform, and the Fourier transform is an extremely powerful tool. However, to use a Fourier approach without justification doesn't mean anything. In particular, I oppose "therefore high frequencies should be removed before sampling." It's mostly right, but there's no proof of any kind that's the best thing to do. Loisel 22:32 Jan 23, 2003 (UTC)
The proof won't fit in the margin. Really, you do need to kill the high frequencies. That's pretty much the whole point of anti-aliasing. AlbertCahalan 00:02, 26 February 2007 (UTC)[reply]
The article is hugely improved, in any case. I agree, the sketch above is (cough) non-rigorous handwaving, but even that was better than the really dodgy article which prompted the comments. Hooray for the Wiki-process, and thanks for your contribution! -- Anon.

I'm a bit confused by the fact it starts by talking about "filters" and frequency-domain stuff but later on just starts averaging multiple samples over each pixel instead. The latter I always thought of as being antialiasing - your pixel's brightness should be the average of what is inside that pixel not just one point within it. The sinc filter, while having the nice property of cutting the high-frequency data off at exactly the Nyquist frequency of the display media, can produce odd fringes either side of sharp edges, it's "nonlocal". —Preceding unsigned comment added by 88.110.208.0 (talk) 05:42, 21 February 2010 (UTC)[reply]

Simple pixel averaging actually leaves some aliasing in the image. A pure high-frequency sine wave, downsampled in this way, would not vanish, as expected, but might turn into a much lower frequency wave that wasn't present in the original image. Of course, because of the averaging, this artifact wave will have much lesser amplitude than without any filtering. Also, besides the sinc and rectangular-in-space (or pixel-averaging) filters there is a much better compromise, which filters out almost all unwanted frequencies and makes almost unnoticeable fringes near the edges. --87.117.185.177 (talk) 21:53, 24 February 2010 (UTC)[reply]

Simple pixel averaging is also a filter having elements of equal value. The image of this filter on frequency domain is the sinc function (surprised :D, they are dual of each other) and it passes the low frequencies well and high frequencies less, so it can also be considered as a non optimal "low pass" filter. Since it eliminates most of the high frequencies, although it will deform the image and leave some aliasing it will work. The reason why it is chosen as a filter is the ease of implementation and low computational cost compared to a sinc like filter. —Preceding unsigned comment added by 24.61.87.72 (talk) 08:20, 29 June 2010 (UTC)[reply]

Etymology[edit]

BTW, what's the exact etymology of the word anti-aliasing ? The fact that two images can be mapped to the same image looks irrelevant to me, as that cannot be avoided (pigeonhole principle tells), and "anti-aliasing" does not specifically try to avoid that either. --FvdP

All sources seem to indicate that the first practical solutions to anti-aliasing were invented Frank Crow, computer graphics pioneer (who incidentally works for nVIDIA these days), in 1977. Earliest reference I could find was: The Aliasing Problem in Computer-Generated Shaded Images, Communications of the ACM, vol. 20(11), pp 799-805. Nov. 1997. Of course I've also seen mentions of work done at the Architecture Machine Group at MIT in 1972, but I have not seen any references to published papers. Chadloder 23:06 Jan 24, 2003 (UTC)
PS here is a link to the article. You must be an ACM member to view the text (I am a member so I will try to distill anything I learn from it). [1] Chadloder 23:09 Jan 24, 2003 (UTC)
I think the term aliasing was used in its radio-engineering sense, related to carrier mixing in a superheterodyne radio: you can hear the same program at two positions on the dial if you don't use prefiltering. If this is the case, the other mathematical/computer science use of the term is inappropriate here (although the pigeonhole info is still relevant). The Anome
I thought the same, and modified the article accordingly. The article at aliasing is nice. --FvdP 00:19 Jan 25, 2003 (UTC)
Right now, I'm having a discussion in Talk:Nyquist-Shannon sampling theorem about the aliasing and Nyquist-Shannon sampling theorem and articles, because I believe that they can be improved. My slant is that I'm a mathematician with some speciality in Fourier series, and I don't entirely agree with the blind-faith-Fourier-series-Frequencies-are-a-God-Given-Thing approach.


More work needed[edit]

This article is getting better all the time: but this is a difficult topic which even confuses experts. More work is needed. The Anome 00:11 Jan 25, 2003 (UTC)

Gamma[edit]

I don't think this passage is pertinent to this article. I am moving it here, it can be restored later. If we were to discuss Gamma correction in here, there's no reason why we wouldn't discuss pixel formats, color theory, interlacing and all these other topics, which do not help at all with anti-aliasing.

(Note that the above assumes that the numerical value of a pixel is proportional to its intensity: for systems where this is not the case, gamma correction must be performed to preserve the linearity of the system, for this approach to hold true).

Loisel 05:31 Jan 25, 2003 (UTC)

Please put it back. Gamma correction problems are the #1 cause of poor anti-aliasing in computer graphics -- doing the A-A computation at the wrong gamma, or displaying the A-A'd image at the wrong gamma, will screw everthing up. <Michael Caine>Not a lot of people know that.</Michael Caine> The Anome

Having worked at SGI and NVidia, I'd say that almost all graphics hardware get the gamma wrong. The only place I've ever seen people complain about it is in film or print, and usually not exactly in those terms because they don't dump the images to the screen, and hence don't have a "gamma" in the final product (although they have to deal with more complicated response curves.) The problem of getting gamma right isn't specific to antialiasing, in fact I would say it affects lighting a whole lot more than antialiasing.

With small pixels, edge antialiasing such as FSAA should only be visible on a small fraction of the pixels (those that are on the edge of a triangle), and for in-triangle AA such as mip-mapping, the adjacent texels are of such a similar color that linear interpolation with or without gamma correction gives almost the same result. Hence, I would argue that being careful with gamma is a whole lot more important for lighting (which affects ALL pixels) than it is with anti-aliasing. And you don't really hear people complaining about how the gamma correction screws up their lighting.

To discuss "frequent problems" with antialiasing, we might need to restructure the article somewhat. Perhaps a section near the end summarizing some related issues. Gamma correction only applies to computer monitors in 8 bits or so per components; perhaps a reference to color theory or some comment about the response curve of the display would be more general. The upcoming graphics hardware should have a flat gamma curve when using floating point framebuffers. Loisel 05:31 Jan 27, 2003 (UTC)

The Anome, do you agree with the placement and wording of the Gamma Correction note now? Loisel 03:25 Jan 28, 2003 (UTC)

It sure does matter. The example images are in fact broken. They get dark near the top, as the checkerboard goes off into the distance. This is wrong. AlbertCahalan 00:02, 26 February 2007 (UTC)[reply]

About images[edit]

Removed "This article certainly needs images!" from Antialiasing article. Created images. Tried to add images. Edit conflict - the new Antialiasing article someone made was merged with this Anti-aliasing article...

What I was going to add:

This image is not antialiased. This image is antialiased.
File:Nonantialiased line and ellipse.png File:Antialiased line and ellipse.png

Unless someone can think of a good use for them, I guess they can be deleted by whoever can delete uploaded files... Cyp 19:08 Feb 12, 2003 (UTC)

Deleted an image from section Full-scene anti-aliasing as it was unprofessional. C Ronald 10:52, 22 March 2007 (UTC)[reply]

Merge[edit]

This was merged in. I think all the information in this stub article is contained in more detail in the current article, so I am moving it to talk. If certain details should be included in the current article, please feel free to integrate them. However, I feel that the language level in the article below is not adequate, and definetly lower than, the language level of the anti-aliasing article. Of course, I am biased, since I wrote most of the anti-aliasing article. Loisel 02:56 Feb 18, 2003 (UTC)

Antialiasing is a graphical effect used to reduce the effect of aliasing (better known as jaggies) in computer graphics.

On a computer lines are drawn in pixels (square dots) the result can look very raw (stairstep-like), depending on the resolution (i.e. the size of the pixels). This stairstep-effect is reduced by surrounding the line with grayscale pixels (black line on white background). You can compare this with a stone stair on which you throw mud and sand as long till you can't see the edges of the steps anymore.

Modern graphic chips like GeForce do this by calculating the gray pixels on their own. See: http://www.nvidia.com/view.asp?IO=feature_hraa

Most modern operating system GUIs (e.g. Windows 2000/XP, Xfree86 on UNIX / GNU) support antialiasing. This is very important for fonts and TFT-Displays. By the way, on TFT-Displays antialiasing is more important since the pixels have a precise square shape. Therefore on TFT subpixel-antialiasing is also used. To increase the optical resolution of a display the color of the neighbour pixels is altered depending on the oriantation of the red, green and blue cells.

Aliasing and radios[edit]

I'm coming very late to this discussion, but I just noticed a glaring error/misconception. The statement " ..the term aliasing was used in its radio-engineering sense, related to carrier mixing in a superheterodyne radio: you can hear the same program at two positions on the dial if you don't use prefiltering" is plain wrong. For one thing, this phenomenon in radio is called imaging, not aliasing - I wrote a small article about this under Image response; yes it arises because of mixing within a superheterodyne receiver, but that is not the same thing as sampling/quantization. Whoever wrote that statement either doesn't understand radio receivers, or antialiasing - one of the two! Secondly, the aliasing in graphics is precisely related to the Nyquist sampling theorem - it is in fact a direct example of it, albeit in two dimensions. It arises because the mathematical description of an object - a line, say, has to be rasterised into a pixel grid array, which is effectively sampling it at a lower rate. If the original object contains frequency components higher than the twice the sampling rate, they will be aliased to new lower frequency positions in the frequency spectrum - this manifests itself as jaggies. GRAHAMUK 03:52 10 Jul 2003 (UTC)


Thanks for the input. I can't say anything about the radio language, because I don't understand it (and that's why I was asking, way above in the talk page, how it worked.) I would appreciate if this matter were elucidated.
However, I did write the mathish/compsci-ish portion of the article. I am a Fourier analyst, and so I have strong opinions about Fourier series and such, and I've written that article very carefully in that respect. The one reference to the "Nyquist sampling theorem" is hidden in this phrase: "By the pigeonhole principle, sometimes two ideal images f(x,y) and g(x,y) will be converted to the same picture on the screen." And yes, I do think that's at the core of the Nyquist sampling theorem.
I could've written more, but there was also an article aliasing which I mostly rewrote. It has a much more detailed explanation of the Fourier version of aliasing. Please see if that corresponds more to your proposition about the Nyquist sampling theorem.
I had a long winded rant about the Nyquist theorem but I decided to remove it before saving, because it's not important. What's more important to me is your remark regarding radio stuff, can we get that straightened out, please?
-- Loisel 08:37 10 Jul 2003 (UTC)
Actually, I found the rest of the article accurate and informative, definitely no problem there, not that my own maths skills is up to criticising it anyway! It was only the paragraph that I quoted I have a problem with, as a (one time) radio engineer. The aliasing article is likewise fine, except that it quotes the same bit about likening the effect to a superhet receiver, so that needs changing too.
To clarify, in a superhet receiver, the input is mixed with a signal from a local oscillator to generate both the sum and difference frequencies, one of which, the intermediate frequency (IF), is selected and amplified by the rest of the receiver. A poorly designed receiver can suffer from the problem of an image of an input signal appearing at another place on the dial by reflection about the IF, and yes, this is a function of the filtering ahead of the mixer stage. However, as far as I can see that's where the similarity ends - the mixing process is not analogous to sampling, and the image is not analogous to the phenomenon of aliasing. I can see why the confusion arises - it sort of looks like the same thing going on - but it isn't. The bottom line is that the statement about radio is wrong, and as such adds only confusion to the article. GRAHAMUK 11:42 10 Jul 2003 (UTC)
Here's the analogy. An RF mixer is essentially a multiplier, multiplying the input signal with the local oscillator. Now consider sampling in the continuous domain, as the multiplication of the input signal with a train of delta functions. There is a clear resemblance here, with an input signal being multiplied with a fixed-frequency signal train. The function of the pre-mixer filter is also directly analogous with the anti-aliasing filter, both of which operate prior to conversion. -- Anon.
I don't understand what that meant, so I can't start throwing my weight around one way or the other. Keep in mind I'm just a mathematician. So an RF mixer is a multiplier -- does that mean that an RF mixer takes in an input signal f(t) and maps it to g(t)f(t) where g is the oscillator, or does it map it to g*f(t), the convolution of g and f (i.e., it's a multiplier in the Fourier analysis lingo?) When you say "in the continuous domain", is that the time domain as opposed to the frequency domain? When you say "train of delta functions" do you mean that g is actually the delta function and the RF mixer operates on f by convolving it with the delta function? Now if that is so, convolution with the point mass is just the identity map, so that wouldn't say much about your RF mixer (it would just say that your RF mixer does nothing at all.) So I'm guessing I've got it wrong. I also don't know what a pre-mixer is or what it does. Loisel 07:46 11 Jul 2003 (UTC)
An RF mixer is a multiplier, true enough. I still don't think that in this context the explanation is a helpful analogy for the phenomenon of antialiasing. I'm still not convinced that it is mathematically equivalent, but even if it is, I don't think the analogy is helpful. It confuses more than enlightens. For one thing, most radio receivers that people will be familiar with don't exhibit the image problem because they have been designed to have a reasonable image response rejection ratio - if an image is detected at all it will usually be put down to the same signal being broadcast more weakly on another frequency. Secondly, without a deep understanding of the maths of the two situations (even if analogous, which I repeat I'm not convinced of yet), most people will not see these two things as being the manifestation of the same phenomenon - jagged graphics sure doesn't LOOK like a phantom radio station! And if one has the maths to see the similarity, then presumably one wouldn't be looking up the explanation of antialiasing in a general purpose encyclopaedia? In other words, even if the analogy makes sense, it will only do so for the type of person for whom this article is NOT written. GRAHAMUK 10:10 13 Jul 2003 (UTC)

I can't fix it, so I'm dropping it here for further discussion.

The term aliasing is used here in its radio-engineering sense, originally used to describe to the phenomenon causing the same transmission to be heard at multiple dial positions on a superheterodyne radio if pre-filtering is not used.

-- Loisel 19:37 14 Jul 2003 (UTC)

Difference between the anti-aliasing figures[edit]


What's the difference between figures 1(b) and 1(c)? The article doesn't even hint at the algorithm of figure 1(b), yet the algorithm of figure 1(c) is "considered better". Isidore 21:51, 29 Aug 2004 (UTC)

The article does explain it, you just have to read further. The algorithm for 1b is explained thus: A better approach is, for each pixel, use the average intensity of a rectangular area in the scene corresponding to the surface area of said pixel. This gives a better, but not yet ideal, "anti-aliased" appearance; figure 1-b was generated this way. The alogorithm for 1c is explained a bit further by making a reference to the sinc filter and the aliasing article. Loisel 11:25, 29 Oct 2004 (UTC)

Gamma-corrected anti-aliased images?[edit]

Speaking of gamma correction, it looks very much like the anti-aliased example images are not gamma-corrected... Anders Kaseorg 03:30, 28 Oct 2004 (UTC)

You are correct. The checkerboard images should not be dark near the top. AlbertCahalan 00:02, 26 February 2007 (UTC)[reply]
Same Goes for the mandelbrot spiral images. Applying gamma 2.2 to each would make them look better, but even better, redo the scaling in liear color space. Orbik (talk) 19:29, 22 November 2010 (UTC)[reply]

Mip-mapping article[edit]

At present this article has far more information about mip-mapping than does the mip-mapping article itself. I believe the text on mip-mapping should be moved to the mip-mapping article and a summary of it should be kept in this article. What do other people think? MIT Trekkie 04:07, 14 Dec 2004 (UTC)

The mipmapping section here is now just a duplicate of the entire mipmapping article. I am removing it and putting in a summary. Valarauka 10:22, 17 September 2006 (UTC)[reply]

"Nyquisty" paragraph[edit]

I might be reading it wrong, but the sentence "It has been observed that to measure a signal of frequency n, you need at least n sample points, and they need to be well-placed." seems to be slightly misleading. It doesn't specify any sort of time within which the n sample points have to be in. Rspanton 00:03, 24 Dec 2005 (UTC)

pronounciation[edit]

how do you pronouce anti aliasing?


ăn'tī (like antimatter, or antidisestablishmentarianism) ā'lē-əs or āl'yəs (like the tv show Alias (TV series)) -ing.

Pictures...[edit]

The layout of the pictures really needs to be sorted - at the moment the page looks untidy and some pictures are nowhere near the text that references them. Romansanders 17:31, 8 April 2006 (UTC)[reply]


Turning anti aliasing off?[edit]

I heard theres a ay to turn anti aliasing off in MS paint, can anyone shed some light on that?

I've never seen AA in MSpaint. I just played with it just now, and there is no AA, period (unless I take off my glasses). 206.252.74.48 (talk) 14:33, 3 January 2008 (UTC)[reply]

If you use the text tool, the text is generally anti-aliased. I don't know of a way of turning this "feature" off, but a workaround is creating the text on a monochrome image (in the attributes window set it to black and white), write your text on that image, then copy and paste from the monochrome image to your colour one. - Rainwarrior (talk) 17:33, 3 January 2008 (UTC)[reply]

New article for Antialiasing (Computer Graphics) ?[edit]

The 'real time approximations' section and its mipmapping subcomponent don't really fit with the tone of the rest of the article, which is more mathematical/theoretical (as it should be). I was thinking I'd create a new article for AA as used specifically in graphics; mipmapping fits there naturally, as does information about supersampling/multisampling, different sample patterns, coverage masks etc. which again shouldn't really go here, and I haven't seen anywhere else. There's already an article at FSAA but it's pretty scanty. Valarauka 20:49, 17 September 2006 (UTC)[reply]

I don't think we need to split the article. Every technique applicable to 2D signals (graphics) can be (and is) used for 1D signals. Mip mapping is not just a graphics technique, it's just most commonly a graphics technique. The same goes the other way for the other techniques. The slower filters are used less in real-time graphics (i.e. games), but they're used plenty in imaging software, etc. A decent article on anti aliasing in "computer graphics" is going to overlap with 95% of what goes in this article. A split is not appropriate. - Rainwarrior 21:53, 17 September 2006 (UTC)[reply]
On second thought, you're probably right. I'm still itchy about the article though... needs improvement. Let's see if I get time. Valarauka 00:48, 18 September 2006 (UTC)[reply]
A lot of articles on wikipedia need improved organization. This one could probably use some as well. - Rainwarrior 06:04, 18 September 2006 (UTC)[reply]

merge with fsaa to here[edit]

I think this article is better than the (already mentioned as small) FSAA (full screen antialiasing) article, and the content should be merged. They are relatively the same thing. I don't think it would hurt this article to include a mention of the methods used in graphics cards, and fsaa could be one of those subheadings. --gatoatigrado 05:48, 4 October 2006 (UTC)[reply]

Isn't mipmapping for textures? --gatoatigrado 05:52, 4 October 2006 (UTC)[reply]

Agreed on both counts. I don't really see that mipmapping has a place in the general article on anti-aliasing - it's a very specific technique to avoid having to do antialiasing in real-time rendering, and it's already covered sufficiently in articles on texturing and texture filtering. - Valarauka(T/C) 05:55, 4 October 2006 (UTC)[reply]

Mip-mapping has a few applications to audio signals, and even in non-realtime graphics there are uses. It is rightly an anti-aliasing technique, not an anti-aliasing "avoidance" technique. - Rainwarrior 15:30, 18 October 2006 (UTC)[reply]
As far as FSAA, it is an application of oversampling, which is an often used anti-aliasing technique. I don't see it being expanded much, so I would support a merge into either this article, or oversampling. - Rainwarrior 15:36, 18 October 2006 (UTC)[reply]

Whats with this sentence?[edit]

Since eyes can rotate in their sockets, this must have to do with the fact that we are dealing with data sampled on a square lattice and not with a continuous image.

What does that have to do with anything? I think this sentence should go. User A1 00:14, 15 December 2006 (UTC)[reply]

Yes, clearly nonsense. Please do get rid of it. Dicklyon 00:36, 15 December 2006 (UTC)[reply]

Is this relevant?[edit]

The section "First-principles approach to anti-aliasing" includes this statement:

"By the pigeonhole principle, sometimes two different ideal images f(x,y) and g(x,y) will be converted to the same picture on the screen. This cannot be avoided."

While that is undoubtedly true, it is not clear how it is relevant. The issue is just the opposite, the fact that a single ideal image can be approximated by many alternative reduced images, which creates the challenge of how to select among them.

Steve Wise 04:57, 7 January 2007 (UTC)Steve Wise[reply]

I think it's completely relevant. Different real images that have the same sample values are aliases of each other. That is, this principle is essentially the definition of aliasing. I'm not sure what you're thinking in your description of "the issue"; I don't see how what you're describing is aliasing. Dicklyon 05:17, 7 January 2007 (UTC)[reply]

Removed image?[edit]

I don't agree that the second image is not related. That is a thumbnail, and you can click to view the larger version. Lugiadoom 08:51, 24 January 2007 (UTC)[reply]

I didn't say it's unrelated, but it's copyright with no good fair-use rationale, and it doesn't make the point as well as the smaller image does. Dicklyon 16:10, 24 January 2007 (UTC)[reply]


Unattributed criticism[edit]

The section that was added about criticism might have some good points, but criticisms need to backed up by an attribution to a sourced. So I took it out. Put it back when it's ready. Dicklyon 16:10, 24 January 2007 (UTC)[reply]

Infinite Detail[edit]

"The idealized image has infinite detail, and is represented by a function f(x,y) where x and y are real numbers defining coordinates."

Infinite or just enough to match the resolution of the human eye? Maybe some elaboration could follow this sentence. --RITZ 04:03, 7 March 2007 (UTC)[reply]

For the purposes of this article, infinite. If you want to know how much detail there actually is, you have to learn quantum physics. For all intents and purposes, the detail is infinite. The human eye has nothing to do with the idealized image. Loisel 00:40, 8 March 2007 (UTC)[reply]


Algorithms[edit]

More should be added about different algorithms, for example Xiaoling Wu's work in the early nineties.


Uh, what?[edit]

"Game consoles and type setting on screen of personal computers employ antialiasing in realtime. Windows Picture and Fax Viewer, Microsoft Powerpoint, Adobe Acrobat Reader, Ghostview, the aqua and aero window managers employ it full screen, while the Gimp and OpenOffice.org Impress are not able to."

That sounds really irrelevant to me. Also like an attempt to discredit and belittle the quality of OpenSource Software, due the wording and the selection of commercial software on one side, the GIMP and OpenOffice on the other side. 217.235.93.78 19:18, 15 July 2007 (UTC)[reply]

Well, I fact tagged it, and then Rainwarrior took it out; so if it comes backs, it will certainly have to be fixed to be in agreement with sources it cites. Problem solved. Dicklyon 21:50, 15 July 2007 (UTC)[reply]
I didn't see the point of any of that information. A comprehensive list of programs that do or do not use anti-aliasing would be gigantic, and of no practical use. Also, "game consoles" is far too unspecific to be true as a general statement; it might be true for the new generation (e.g. Microsoft put anti-aliasing on the XBox 360's Technical Requirements Checklist), but definitely wasn't in the not too distant past (the difference on your average television was probably too negligible to be important). - Rainwarrior 04:17, 16 July 2007 (UTC)[reply]
The potential value would be in knowing what platforms or APIs support what kind of anti-aliasing. If there's a source for such info, the list shouldn't so open-ended as a list of apps. Dicklyon 04:42, 16 July 2007 (UTC)[reply]
Someone may be thinking about Microsoft's Cleartype technology, which is an interesting form of antialiasing, but a correct comment should be included. DonPMitchell (talk) 22:30, 5 July 2008 (UTC)[reply]

Ideal low-pass filter[edit]

"The goal of sharply cutting off frequencies above a certain limit, known as the Nyquist frequency, can not be realized exactly, even with Fourier techniques, so it is always approximated, with many different choices of detailed algorithm".

I believe the above statement is wrong and should be removed or rephrased. Could you please justify why can you not achieve a sharp cut-off on a discrete signal of finite length such as a computer image. Maybe you are referring to the ringing artifacts (Gibbs phenomenon) which are a consequence of a sharp cut-off? --xerm (talk) 11:59, 15 February 2008 (UTC)[reply]

Dear Ermilios,
The problem with the anti-aliasing article and its cousin, the aliasing article, is that every well-meaning gamer, engineer and scientist has some idea of how things work. This topic has a mathematical side, and a popular side. (And maybe an engineering side, somewhere between the two.) Because these two or three aspects coexist within the same article, it becomes quite daunting to keep everything straight.
Certainly, I think that User:Dicklyon has been putting a lot of good work into aliasing and anti-aliasing. Dicklyon also thinks that s/he is an expert in the field (see Talk:Aliasing#Expert_needed.)
I think it's possible that Dicklyon is a top notch engineer or other type of scientist, but I don't think that s/he's an expert in the field. (I hope I'm not going to offend you, Dicklyon!)
In the case that you point out, s/he's the one that inserted the passage you refer to. [2]
As you point out, the passage doesn't actually make any sense.
Maybe because I spend most of my time deep in articles that nobody else ever looks at (such as finite element method), I don't have to deal with this stuff a lot, so I usually don't. In the case of this article, while I wrote most of it originally, I don't really keep an eye very much on it anymore.
Loisel (talk) 20:01, 15 February 2008 (UTC)[reply]
I just checked Dicklyon's user page and web page. So I understand why he claims to be an expert, and certainly I'm sure he's an expert in the engineer/graphics stuff. However, I don't think he fully understands what's going on with aliasing and anti-aliasing. (Again, I hope I don't offend!)
Loisel (talk) 20:21, 15 February 2008 (UTC)[reply]
The key to the statement was the "exactly". No filter can be perfectly sharp. The point was just that some approximation must always be involved, because people sometimes get the impression that that's not the case. Do either of you disagree? There may be more clear ways to put it, so feel free to work on it. And yes, I'm an expert, but that's not something that needs to enter into the discussion. Dicklyon (talk) 00:02, 16 February 2008 (UTC)[reply]
I think I see what you're getting at, Ermilios, when you say "a discrete signal of finite length such as a computer image." You're assuming you already have a sampled image, so you can treat is having zero energy above its Nyquist frequency already (treating the underlying image as periodically repeating, so it has finite Fourier series); in that case, the infinite length of a sinc filter can be reduced to finite sums for resampling the image with perfectly sharp anti-aliasing filter. But that's not the interesting case. Dicklyon (talk) 00:17, 16 February 2008 (UTC)[reply]

You can resample a digital image with filters. But in computer graphics, the initial rendering operation involves sampling what I called a "symbolic image" represented by some scene description, and in general there is no way to pre-filter that symbolic scene representation before it is sampled (e.g. by rasteriztion or ray tracing). Take a look at a tutorial I wrote for SIGGRAPH '90: http://www.mentallandscape.com/Papers_siggraph90tutorial.pdf DonPMitchell (talk) 20:13, 5 July 2008 (UTC)[reply]

OK, this isn't mentioned so often, but perfect Nyquist sampling, allowing exact reproduction from a sampled signal, only works for either an infinite number of samples, or a perfectly periodic signal. With a finite number of sample points, Nyquist works close enough, but not exactly. With an infinite number of sample points, you can approximate, but not exactly make, an infinitely sharp filter. Gah4 (talk) 23:06, 8 September 2019 (UTC)[reply]

Dropped proposal to merge with Temporal anti-aliasing[edit]

The following discussion is closed. Please do not modify it. Subsequent comments should be made in a new section. A summary of the conclusions reached follows.
The result of this discussion was that after about nine months of silence, the proposer renamed this article from Anti-aliasing to Spatial anti-aliasing in this revision. --SamB (talk) 20:31, 8 April 2011 (UTC)[reply]

I'm suggesting merging the small amount of content at Temporal anti-aliasing into this article, as the underlying principles are identical. Whilst it's the case that this article is currently dedicated solely to spatial anti-aliasing in the context of computer graphics, there's no reason it should be limited to just this. A wider exposition of the field is needed. Alternatively, this article should be renamed to Spatial anti-aliasing in computer graphics or similar. Oli Filth(talk|contribs) 17:54, 31 May 2009 (UTC)[reply]

  • Oppose - Two very different concepts. Completely different problems with different solutions. Both articles do need to be expanded. Renaming this article is also not appropriate, as anti-aliasing is the generally accepted term, Spatial anti-aliasing would only add confusion. A "See also" link is sufficient.--Knulclunk (talk) 01:46, 13 August 2009 (UTC)[reply]
    • These concepts are mathematically identical, it's just a different domain (as Dicklyon has already pointed out below). My rename suggestion was meant somewhat tongue-in-cheek; I was merely highlighting that the scope of this article is currently far narrower than its title suggests. Oli Filth(talk|contribs) 18:39, 13 August 2009 (UTC)[reply]
  • Support – According to the lead on this article, it covers various forms of anti-aliasing already, including temporal (waveform) anti-aliasing. This article temporal anti-aliasing is really just about "Temporal anti-aliasing in computer generated moving imagery", which is rather narrow, and could easily be covered by a section here instead of a separate article. That little stub of an article has been stagnant, unreferenced, and nearly orphan since 2006; let's adopt it. Dicklyon (talk) 02:11, 13 August 2009 (UTC)[reply]
I think better to combine Temporal anti-aliasing with either Wagon-wheel effect or Motion blur, but better still to expand expand the article and avoid a merge all together.--Knulclunk (talk) 13:01, 13 August 2009 (UTC)[reply]
  • Oppose. As Knulclunk says, it's a different problem with different solutions. Both are big topics with plenty of material for their own articles. Merging would not be an improvement nor even a good stopgap for the lack of good coverage on the temporal side. —David Eppstein (talk) 06:12, 13 August 2009 (UTC)[reply]
I'd say it's the same problem, in a different domain, with similar types of solutions. What sources do you know that treat it as a different problem with different solutions? A merge would be a good step toward treating this topic. The wagon-wheel effect article is about aliasing, not how to fix it; the motion blur article related, since motion blur can be used as an anti-aliasing filter, but that article's focus is quite different, being applicable to stills and non-aliasing-related visual effects in general. Dicklyon (talk) 16:42, 13 August 2009 (UTC)[reply]
These are not purely mathematical problems, but problems involving human perception, and the perceptual issues with these two types of aliasing are very different, leading to different mathematical formulations and different algorithmic solutions. Blurring the distinction between the two would be a mistake. —David Eppstein (talk) 19:06, 13 August 2009 (UTC)[reply]
Well in that case, under the current title (Anti-aliasing), this article ought to focus on the common aspects (anything derived directly from LTI theory and the sampling theorem is common to all types of aliasing). Any specifics should either be mentioned in separate articles (e.g. Temporal anti-aliasing, Spatial anti-aliasing, Audio anti-aliasing), or everything should be merged into this article. As it stands, the content is unbalanced. Oli Filth(talk|contribs) 19:15, 13 August 2009 (UTC)[reply]
Unbalanced? Is this a controversial issue? Is there a rash of confusion?--Knulclunk (talk) 22:59, 13 August 2009 (UTC)[reply]
It is unbalanced because this article currently is "dedicated to anti-aliasing methods in computer graphics" (quote from article lead). Why so?
If, as you say, anti-aliasing in time and space are so different, why does the "anti-aliasing" article only deal with one of them? Oli Filth(talk|contribs) 23:07, 13 August 2009 (UTC)[reply]
I suppose that since this article is semi summary style, vectoring off the anti-aliasing filter in the lead for the typical waveform case (and also the photographic imaging case), we could consider going further that way and making a cleaner summary-style article that dispatches to all the more specific topics. Dicklyon (talk) 00:21, 14 August 2009 (UTC)[reply]

(outdent) Per the discussions above, I've now moved the article to Spatial anti-aliasing, as that is the only correct title given the article's content. Oli Filth(talk|contribs) 17:38, 16 May 2010 (UTC)[reply]

The discussion above is closed. Please do not modify it. Subsequent comments should be made on the appropriate discussion page. No further edits should be made to this discussion.

Wrong pictures[edit]

Pictures are in some strange non-linear color space, instead of sRGB. 83.4.200.31 (talk) 20:34, 4 January 2010 (UTC)[reply]

Jaggies ???[edit]

In the FSAA section "jaggies" are considered to be the only aliasing effect which is NOT correct. In fact there are effects like "moire" or loosing edges, curves(some high frequency geometry) altogether rather then having "jagged" edges. Unfortunately people have a false perception of "aliasing = jagged edges" because of this false treatment of the subject. Please correct it. —Preceding unsigned comment added by 24.61.87.72 (talk) 21:10, 29 June 2010 (UTC)[reply]

While there are a variety of aliasing effects, computer generated graphics anti aliasing (such as FSAA) ONLY deals with juggies, and not those other effects. (keep in mind, that as a fully artificial image, it does not actually HAVE many of the artifacts found in photography/video recording. While at the same time, juggies are exclusive to computer generated graphics. --Taltamir (talk) 22:07, 10 January 2011 (UTC)[reply]

Morphological Anti Aliasing[edit]

How about Morphological anti-aliasing which is coming into effect as the new Radeon 6000 series releases? Some of it is discussed in this article: http://www.tomshardware.com/reviews/radeon-hd-6870-radeon-hd-6850-barts,2776-4.html IOA94 (talk) 20:32, 1 November 2010 (UTC)[reply]

Is Morphological anti-aliasing abreviated to MLAA? Because MLAA redirects to this article but is nowhere mentioned. --145.120.12.196 (talk) 20:06, 4 April 2012 (UTC)[reply]
MLAA is indeed the abbreviation of Morphological anti-aliasing. I do hope that the article is expanded to mention it. Since there are already articles for FXAA and [[MSAA]|, it might even make sense to create a dedicated article for MLAA. Norrk (talk) 12:46, 25 November 2012 (UTC)[reply]

Signal processing in the ear[edit]

Is the line "The ear is predominantly sensitive to lower frequencies. And so, in signal processing, we choose to eliminate all high frequencies from the signal, keeping only the frequencies that are low enough to be sampled correctly by our sample rate." strictly necessary and in context? Evn2-NJITWILL (talk) 20:22, 23 November 2010 (UTC)[reply]

The ear was pretty irrelevant in that discussion, but a lot more was wrong, too. In this edit, I tried to clean it up and remove the nonsense. The section assumed that the sampling theorem had a converse, and that an ideally sharp filter would be best for image anti-aliasing; neither is true. Dicklyon (talk) 04:56, 28 November 2010 (UTC)[reply]

FSAA[edit]

I have not been able to find any information anywhere on the internet about FSAA, it is "sourced" with only one link, but the article in that link NEVER mentions the term FSAA, meaning it has no sourcing at all. --Taltamir (talk) 22:17, 10 January 2011 (UTC) Note, that while unable to find information about what it means or what it is, I have found mention of the term. For example here: http://www.nvidia.com/object/quadro_sli_fsaa.html nvidia clearly uses the term FSAA, just not in the one source given for that portion of the article. So if anyone could find better sources for it, please do.--Taltamir (talk) 22:21, 10 January 2011 (UTC)[reply]

I found and added a couple of sources and removed the one that doesn't seem to mention it. Dicklyon (talk) 05:36, 11 January 2011 (UTC)[reply]
Thank you. This raises another issue... The link you provided explains what FSAA is, and it is just SSAA 2x. On the other hand, I found a source that explains it simply describes MSAA.
This book specifies that FSAA is just SSAA 2x. (render at 2x height, 2x width, and then downscale) http://books.google.com/books?id=LJ20tsePKk4C&pg=PA442
This web article specifies that FSAA is MSAA. ]http://homepage.mac.com/arekkusu/bugs/invariance/FSAA.html --Taltamir (talk) 22:46, 12 January 2011 (UTC)[reply]
Beats me. I don't know what MSAA and SSAA are. Dicklyon (talk) 02:46, 13 January 2011 (UTC)[reply]
I have been investigating what the various AA terms mean and compiled my findings here: http://forums.anandtech.com/showthread.php?p=30995870
There you can find an explanation on what MSAA and SSAA are.--Taltamir (talk) 01:24, 29 January 2011 (UTC)[reply]

Digital photography[edit]

Is this article supposed to be only about anti-aliasing in graphical display systems? Anti-alias (low pass) spatial filters are a part of many digital cameras, needed to prevent aliasing due to the spatial sampling of the image sensor. There is a little in the anti-aliasing filter page, but not so much. Given the title of this page, it should include optical (spatial) low-pass anti-alias filters, too. Gah4 (talk) 21:20, 17 August 2017 (UTC)[reply]

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Is this the same as downscaling and downsizing?[edit]

A few TV station articles, e.g. TV Land refer to downscaling: "Picture Format: 1080i HDTV (downscaled to letterboxed 480i for the SDTV feed)". By "downscaling" do they mean spatial anti-aliasing? I would like to add have added a WP:HATNOTE to Downscaling - directing readers to this article if they are interested in image downscaling - but I want to be sure I have got it right.

On a related note, this article is linked to from the dab page Downsizing, with the (uncited) comment "Downsizing the image : resizing the image to lower pixel resolution for reduce the file size or Spatial_anti-aliasing". If downsizing and downscaling are alternative terms for spatial anti-aliasing, this article should say so. Adpete Adpete (talk) 23:12, 22 December 2021 (UTC)[reply]

Downscaling has to include a low-pass filter to prevent aliasing. It doesn't sound quite right to say that it is spatial anti-aliasing. They are related, but that doesn't mean that one is the other. Gah4 (talk) 11:34, 24 December 2021 (UTC)[reply]
Thanks. Does that comment also apply to downsizing, i.e. are downsizing and downscaling pretty well synonyms when it comes to computer graphics? Adpete (talk) 00:30, 25 December 2021 (UTC)[reply]
Downsizing is mostly used when empty nesters move to a smaller house or condo. In the current case, I believe it could also apply to cropping. I don't know quite well enough how it is popularly used. Gah4 (talk) 12:31, 25 December 2021 (UTC)[reply]
After looking around a bit, I have found the Image scaling article. It seems to me that Image scaling, rather than this article, is the correct place to start for image downscaling; and so is the best place for the hatnote at Downscaling, and the link at the Downsizing dab page. Would you agree? (p.s. Currently the Downscaling article is about the techniques for increasing the resolution in climate modelling. It would of course be ok to have separate articles called something like Downscaling (climate modelling) and Downscaling (video image), but I have very little expertise in the latter so I am not volunteering). Adpete (talk) 04:47, 27 December 2021 (UTC)[reply]
Sounds fine to me. You might also be interested in Deconvolution. Gah4 (talk) 11:45, 27 December 2021 (UTC)[reply]