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Resampling

is an option that specifies the method to be used for resampling images or arrays.

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Examples  
Basic Examples  
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Tech Notes
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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" CatmullRom (Meijering) cubic polynomial interpolation
    "German" German polynomial interpolation
    {"Hermite",n} ^(th)-order Hermite interpolation
    {"Schaum",n} ^(th)-order Schaum (Lagrange) polynomial interpolation
    {"Meijering",n} odd ^(th)-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 , )

Examples

Basic Examples  (2)

Downsample an image using Gaussian interpolation:

Upsample an image using a higher-order interpolation:

Tech Notes

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

BibTeX

@misc{reference.wolfram_2025_resampling, author="Wolfram Research", title="{Resampling}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/Resampling.html}", note=[Accessed: 16-November-2025]}

BibLaTeX

@online{reference.wolfram_2025_resampling, organization={Wolfram Research}, title={Resampling}, year={2014}, url={https://reference.wolfram.com/language/ref/Resampling.html}, note=[Accessed: 16-November-2025]}

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