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An example of spatial aliasing is the moiré pattern observed in a poorly pixelized image of a brick wall. Spatial anti-aliasing techniques avoid such poor pixelizations. Aliasing can be caused either by the sampling stage or the reconstruction stage; these may be distinguished by calling sampling aliasing prealiasing and reconstruction ...
Aliasing can occur in any language that can refer to one location in memory with more than one name (for example, with pointers).This is a common problem with functions that accept pointer arguments, and their tolerance (or the lack thereof) for aliasing must be carefully documented, particularly for functions that perform complex manipulations on memory areas passed to them.
Type aliasing is a feature in some programming languages that allows creating a reference to a type using another name. It does not create a new type hence does not increase type safety . It can be used to shorten a long name.
Effects of aliasing or blurring can occur when the lens MTF and sensor MTF are mismatched. When the optical image which is sampled by the sensor device contains higher spatial frequencies than the sensor, the under sampling acts as a low-pass filter to reduce or eliminate aliasing.
Aliasing is an automatic and unavoidable result of observing such a fraction. [3] [4] The aliasing properties of a design are often summarized by giving its resolution. This measures the degree to which the design avoids aliasing between main effects and important interactions. [5]
An anti-alias filter quite tight to the FM radio band is required, and there's not room for stations at nearby expansion channels such as 87.9 without aliasing. Spectrum of the FM radio band (88–108 MHz) and its baseband alias under 56 MHz ( n = 4) sampling, showing plenty of room for bandpass anti-aliasing filter transition bands.
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The bandwidth, B, in this example is just small enough that the slower sampling does not cause overlap (aliasing). Sometimes, a sampled function is resampled at a lower rate by keeping only every M th sample and discarding the others, commonly called "decimation". Potential aliasing is prevented by lowpass-filtering the samples before decimation.