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ifft_2d.cpp
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ifft_2d.cpp
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// Software: Inverse Fast Fourier Transform 2D (for real original signals only)
// Author: Hy Truong Son
// Position: PhD Student
// Institution: Department of Computer Science, The University of Chicago
// Email: [email protected], [email protected]
// Website: http://people.inf.elte.hu/hytruongson/
// Copyright 2016 (c) Hy Truong Son. All rights reserved.
// Time complexity: O(N^2logN)
// Space complexity: O(N^2)
#include <iostream>
#include <fstream>
#include <sstream>
#include <cstring>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include <vector>
#include <set>
#include <iterator>
#include <algorithm>
#include <ctime>
#include "mex.h"
using namespace std;
void vector2matrix(double *input, int nRows, int nCols, double **output) {
for (int i = 0; i < nRows; ++i) {
for (int j = 0; j < nCols; ++j) {
output[i][j] = input[j * nRows + i];
}
}
}
void matrix2vector(double **input, int nRows, int nCols, double *output) {
for (int i = 0; i < nRows; ++i) {
for (int j = 0; j < nCols; ++j) {
output[j * nRows + i] = input[i][j];
}
}
}
// Fast Fourier Transform 1D (with the different harmonic coefficient) for complex signals
// It becomes the Inverse Fast Fourier Transform 1D
void iFFT(double *Re_Signal, double *Im_Signal, double *Re_F, double *Im_F, int N, int t) {
if (N == 1) {
Re_F[0] = Re_Signal[0];
Im_F[0] = Im_Signal[0];
return;
}
int half = N / 2;
iFFT(Re_Signal, Im_Signal, Re_F, Im_F, half, 2 * t);
iFFT(Re_Signal + t, Im_Signal + t, Re_F + half, Im_F + half, half, 2 * t);
for (int k = 0; k < half; ++k) {
double r1 = Re_F[k];
double i1 = Im_F[k];
double r2 = Re_F[k + half];
double i2 = Im_F[k + half];
double alpha = 2.0 * M_PI * (double)(k) / (double)(N);
double r3 = cos(alpha);
double i3 = sin(alpha);
double r4 = r2 * r3 - i2 * i3;
double i4 = r3 * i2 + r2 * i3;
Re_F[k] = r1 + r4;
Im_F[k] = i1 + i4;
Re_F[k + half] = r1 - r4;
Im_F[k + half] = i1 - i4;
}
}
void mexFunction(int nOutputs, mxArray *output_pointers[], int nInputs, const mxArray *input_pointers[]) {
if (nInputs != 2) {
std::cerr << "The number of input parameters must be exactly 2 (real and imaginary parts)!" << std::endl;
return;
}
if (nOutputs != 1) {
std::cerr << "The number of output parameters must be exactly 1 (only for the real signal)!" << std::endl;
return;
}
if ((mxGetM(input_pointers[0]) != mxGetM(input_pointers[1])) || (mxGetN(input_pointers[0]) != mxGetN(input_pointers[1]))) {
std::cerr << "The real and imaginary parts must have the same size!" << std::endl;
return;
}
// M: number of rows
// N: number of columns
int M = mxGetM(input_pointers[0]);
int N = mxGetN(input_pointers[0]);
// Memory allocation
double **s = new double* [M]; // The original signal
double **Re_F = new double* [M]; // Its Fourier transform
double **Im_F = new double* [M]; // Its Fourier transform
double **Re_H = new double* [M]; // Temparary matrix
double **Im_H = new double* [M]; // Temparary matrix
for (int row = 0; row < M; ++row) {
s[row] = new double [N];
Re_F[row] = new double [N];
Im_F[row] = new double [N];
Re_H[row] = new double [N];
Im_H[row] = new double [N];
}
// Initialization
vector2matrix(mxGetPr(input_pointers[0]), M, N, Re_F);
vector2matrix(mxGetPr(input_pointers[1]), M, N, Im_F);
// Normalization constant
double c = 1.0 / sqrt(M * N);
// Fast Fourier Transform 2D - Precomputation
for (int x = 0; x < M; ++x) {
iFFT(Re_F[x], Im_F[x], Re_H[x], Im_H[x], N, 1);
}
// Fast Fourier Transform 2D - Computation
double *Re_h = new double [M];
double *Im_h = new double [M];
double *Re_s = new double [M];
double *Im_s = new double [M];
for (int v = 0; v < N; ++v) {
for (int x = 0; x < M; ++x) {
Re_h[x] = Re_H[x][v];
Im_h[x] = Im_H[x][v];
}
iFFT(Re_h, Im_h, Re_s, Im_s, M, 1);
for (int u = 0; u < M; ++u) {
s[u][v] = Re_s[u] * c;
}
}
// Return outputs
output_pointers[0] = mxCreateDoubleMatrix(M, N, mxREAL);
matrix2vector(s, M, N, mxGetPr(output_pointers[0]));
}