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FFT2 optimization

version (1.96 KB) by Luigi Rosa
Speed up FFT2.

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Updated 07 Mar 2005

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FFT2 optimization.

Many image processing applications require an extensive usage of FFT2 routine (or, in the most general case, a N-dimensional FFT) of matrices having the same dimensions. In these cases MATLAB FFT2 can result extremely inefficient. In general the execution time can be significantly reduced by splitting the N-dimensional FFT into several unidimensional FFT. A good trick is to apply the fft operator varying the minimum number of times the length of the unidimensional vectors which have to be FFT-transformed. You might be able to increase the speed of fft using the utility function fftw, which controls how MATLAB optimizes the algorithm used to compute an FFT of a particular size and dimension. In the following examples the planner is always 'hybrid'. The best vectorization strongly depends on the dimensions of input matrices. Chose the optimal solution comparing the execution times of the methods proposed.

Luigi ROSA
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Cite As

Luigi Rosa (2020). FFT2 optimization (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (2)

Benjamin Auffarth

It slows down. Speed improvement is negative.

Donato Pace

this problem is still present in MATLAB 7.1???

MATLAB Release Compatibility
Created with R14SP1
Compatible with any release
Platform Compatibility
Windows macOS Linux