Resampling
Resampling
is an option that specifies the method to be used for resampling images or arrays.
Details
- In all of the interpolations, the window is normalized so that its values sum to 1.
- With the setting Resampling->Automatic, the method of resampling is selected automatically.
- Specific settings for Resampling are typically used to achieve different tradeoffs with respect to prefiltering of data, order of interpolation, and complexity of computation.
- Nearest neighbor resamplings are fast, and except for "Nearest" do not introduce any new values:
-
"Nearest" nearest neighbor, use average for tie "NearestLeft" nearest neighbor, use left for tie "NearestRight" nearest neighbor, use right for tie - Spline interpolations are relatively fast, based on polynomial interpolation of order
with 
continuous derivatives: -
"Constant" piecewise constant interpolation "Linear" piecewise linear interpolation "Quadratic" spline interpolation of order 2 "Cubic" spline interpolation of order 3 "Quartic" spline interpolation of order 4 "Quintic" spline interpolation of order 5 {"Spline",n} spline interpolation of order up to 
- Gaussian and B-splines of higher orders are practically isotropic resamplings. They are fast approximations that blur the data rather than interpolations:
-
"Gaussian" Gaussian weighted resampling using 
and 
{"Gaussian",r,σ} Gaussian with a specific radius 
and sigma 
{"BSpline",n} B-spline approximation of order up to 
- Classic polynomial interpolations up to order
: -
"Dodgson" Dodgson polynomial interpolation {"Keys",a} Keys polynomial interpolation (default 
)"CatmullRom" Catmull–Rom (Meijering) cubic polynomial interpolation "German" German polynomial interpolation {"Hermite", 
}
-order Hermite interpolation{"Schaum",n} 
-order Schaum (Lagrange) polynomial interpolation{"Meijering",n} odd 
-order Meijering polynomial interpolation - Optimal sampling of maximal order and minimal support (o-MOMS) gives the best resampling for a given order, and may give only continuous or even discontinuous filter kernel:
-
{"OMOMS",n} o-MOMS of order up to 
- Windowed sinc interpolations give ideal resamplings regularized by windows of the form
or 
. The following possible window specifications can be given: -
{"Bartlett",r} Bartlett (default 
){"Blackman",r} Blackman (default 
){"Connes",r,α} Connes (default 
, 
){"Cosine",r,α} cosine (default 
, 
){"Hamming",r} Hamming (default 
){"Hann",r,α} Hann (default 
, 
){"Kaiser",r,α} Kaiser (default 
, 
){"Lanczos",r} Lanczos (default 
){"Parzen",r} Parzen (default 
){"Welch",r,α} Welch (default 
, 
)
Wolfram Research (2010), Resampling, Wolfram Language function, https://reference.wolfram.com/language/ref/Resampling.html (updated 2014).
Text
Wolfram Research (2010), Resampling, Wolfram Language function, https://reference.wolfram.com/language/ref/Resampling.html (updated 2014).
CMS
Wolfram Language. 2010. "Resampling." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2014. https://reference.wolfram.com/language/ref/Resampling.html.
APA
Wolfram Language. (2010). Resampling. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/Resampling.html