laplacian_conv2.cpp 1.58 KB
#include <stim/image/image.h>
#include <cmath>
#include <stim/visualization/colormap.h>
#include <stim/image/image_contour_detection.h>

#define PI 3.1415926

void array_multiply(float* lhs, float rhs, unsigned int N);
void array_add(float* ptr1, float* ptr2, float* sum, unsigned int N);
void array_abs(float* img, unsigned int N);

/// This function evaluates the center-surround(Laplacian of Gaussian) gaussian derivative gradient of an one-channel image

/// @param img is the one-channel image
/// @param r is an array of radii for different scaled discs(filters)
/// @param sigma_n is the number of standard deviations used to define the sigma

stim::image<float> Gd_center(stim::image<float> image, int r, unsigned int sigma_n){

unsigned int w = image.width();    // get the width of picture
unsigned int h = image.height();   // get the height of picture
unsigned N = w * h;				   // get the number of pixels of picture
int winsize = 2 * r + 1;           // set the winsdow size of disc(filter)

stim::image<float> I(w, h, 1, 2);       // allocate space for return image of Gd2
stim::image<float> Ixx(w, h);       // allocate space for Ixx
stim::image<float> Iyy(w, h);       // allocate space for Iyy
stim::image<float> Gd_center(w, h);       // allocate space for Pb

I = Gd2(image, r, sigma_n);  // calculate the Ixx, Iyy
Ixx = I.channel(0);
Iyy = I.channel(1);

array_add(Ixx.data(), Iyy.data(), Gd_center.data(), N);				//Gd_center = Ixx + Iyy;
array_abs(Gd_center.data(), N);

//stim::cpu2image(Gd_center.data(), "data_output/Gd_center_0919.bmp", w, h, stim::cmBrewer);

return Gd_center;

}