Brian

Hello Michael,

it has a slightly different feature set.
The differences are:
- No support for X, Y, you have to do that yourself to the XI and YI variables.
  That behaviour is what I need most often, and it saves a few cycles.
- Support for Z with dimensions HxWxD1xD2x..., returning Z(XI,YI,:,:,:,...) in slightly abused notation. I.e. it treats the dimensions following the first two dimensions as vectors and interpolates these. This is useful for color image interpolation, where you have arrays of size [H x W x 3].

I hope that helps,

Brian

Hello Courtney,

the file is actually working well for me with gnu c++ compiler and intel compiler. If you could state the errors you receive under windows, I might be willing to fix it.

When I use mex -largeArrayDims to compile this function, the results are wrong (all zero). It works OK without this switch, though -largeArrayDims will probably become mandatory soon!

Matlab R2009a, Visual Studio 2008 SP1, Win7 x64 bit Enterprise.

Anyway, I really appreciate your work. Saved me a lot of time from coding this myself!

Linear interpolation is faster and cubic is much faster, However the slice shown has more data then what we usually get by using matlab function Interp3.
For some applications you might want to have same looking slice but much faster, I customized it for my application, cubic is almost 60%-70% faster then intep3 with mri data set of matlab.
Very cool contribution, thanks for uploading this :-)

Hello Michael,

it has a slightly different feature set.
The differences are:
- No support for X, Y, you have to do that yourself to the XI and YI variables.
  That behaviour is what I need most often, and it saves a few cycles.
- Support for Z with dimensions HxWxD1xD2x..., returning Z(XI,YI,:,:,:,...) in slightly abused notation. I.e. it treats the dimensions following the first two dimensions as vectors and interpolates these. This is useful for color image interpolation, where you have arrays of size [H x W x 3].

I hope that helps,

Brian