FFT2FS_2D: Two Dimenstional Fourier Expansion

In FPCA2D: Two Dimensional Functional Principal Component Analysis

Description

Conduct the two dimensional Fourier expansion by using fast Fourier transformation.

Usage

FFT2FS_2D(A)

Arguments

A	A is a two dimensional numerical matrix.

Details

Conduct the two dimensional Fourier expansion by using fast Fourier transformation. To make the results comparable, be sure to transform all the intensity values of each image pixel should be between 0 and 1.

Value

C	The two dimensional Fourier expansion of the input matrix

References

Lin N, Jiang J, Guo S, Xiong M (2015) Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis. PLoS ONE 10(7): e0132945. doi:10.1371/journal.pone.0132945

Examples

   ## Not run: 
   A = matrix(sample(seq(0,1,0.01),100),nrow=10)
   rlt = FFT2FS_2D(A)
           
## End(Not run) 

FPCA2D documentation built on May 2, 2019, 12:36 p.m.