<p>What do you mean by &quot;normal&quot; aliasing?  Aliasing is the result of under-sampling: i.e being given a signal with a high frequency (temporal and/or spatial) that is being sampled too infrequently (it needs to be sampled at a rate exceeding 2x its maximum frequency OR band-limited/pre-filtered until its max frequency is &lt; 1/2 the sampling rate).</p>
<p>With texture data, <em>the</em> common pre-filtering approach is to use MIP maps (see <a href="https://dl.acm.org/doi/10.1145/800059.801126" rel="nofollow noreferrer">Lance Williams' &quot;Pyramidal Parametrics&quot;</a>.</p>
<p>FWIW I like to explain aliasing by the following:<br>
Imagine you work for a an office-based company (i.e pre covid WFH etc), and are at your desk solidly, 9~5, apart from a lunch break and a 15 min coffee break at 10:30.
The CEO take a regular stroll around the office at 10:35 and thus always sees you in the kitchen, rather than at your desk.
Because she is under-sampling your 'signal', she thus assumes you are never working.</p>

CC BY-SA 4.0
2023-01-12T11:00:59.533Z
Thank you for this answer. I was actually a bit confused about aliasing itself. That is why I framed the question poorly.
Academic
CC BY-SA 4.0
2023-01-11T08:51:53.740Z
2023-01-16T14:52:55.457Z
2023-01-16T14:52:55.457Z
Simon F
<p>Is there any specific difference from normal aliasing and specifically <strong>texture aliasing?</strong></p>
<p>Also, is there any specific data structure which can be used to avoid aliasing?</p>

<antialiasing>
What is texture aliasing and is there any specific "data-structure" to avoid it
Academic
# What is texture aliasing and is there any specific "data-structure" to avoid it

(Asked by: username_0 on 2023-01-11)

Is there any specific difference from normal aliasing and specifically **texture aliasing?**

Also, is there any specific data structure which can be used to avoid aliasing?

**Tags:** antialiasing


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## 1 answers

### Answer by username_1 on 2023-01-11. Score: 2 | Accepted answer

What do you mean by "normal" aliasing? Aliasing is the result of under-sampling: i.e being given a signal with a high frequency (temporal and/or spatial) that is being sampled too infrequently (it needs to be sampled at a rate exceeding 2x its maximum frequency OR band-limited/pre-filtered until its max frequency is < 1/2 the sampling rate).

With texture data, *the* common pre-filtering approach is to use MIP maps (see [Lance Williams' "Pyramidal Parametrics"](https://dl.acm.org/doi/10.1145/800059.801126).

FWIW I like to explain aliasing by the following:  
Imagine you work for a an office-based company (i.e pre covid WFH etc), and are at your desk solidly, 9~5, apart from a lunch break and a 15 min coffee break at 10:30.
The CEO take a regular stroll around the office at 10:35 and thus always sees you in the kitchen, rather than at your desk.
Because she is under-sampling your 'signal', she thus assumes you are never working.

> **Comments:**
> **username_0**: Thank you for this answer. I was actually a bit confused about aliasing itself. That is why I framed the question poorly.  

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