b71cc8bb
 Tianshu Cheng
mPb using 3 channels
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#include <stim/image/image.h>
#include <cmath>
#include <stim/visualization/colormap.h>
#include <stim/image/image_contour_detection.h>
#include <iostream>
void main()
{
stim::image<float> rgb,gaussgradient; //generate an image object
rgb.load("101087.bmp"); //load the input image
unsigned int w = rgb.width(); //get the image size
unsigned int h = rgb.height();
unsigned int s = rgb.size();
unsigned a = sizeof(float);
stim::image<float> lab; //create an image object for a single-channel (grayscale) image
lab = rgb.srgb2lab(); //create the single-channel image
/*
stim::image<float> pic_light, pic_colora, pic_colorb;
pic_light = lab.channel(0);
pic_light.save("pic_light.bmp");
pic_colora = lab.channel(1);
pic_colorb = lab.channel(2);
float sigma = 2;
unsigned int sigma_n = 3;
unsigned int r = 5;
unsigned int winsize = r * 2; //window size = winsize + 1
float theta = 90;
gaussgradient = gaussian_derivative_filter_odd(pic_colorb, sigma, sigma_n, winsize, theta, w, h);
gaussgradient.save("data_output/pic_gray_gradient.bmp");
*/
//float theta = 0;
unsigned int theta_n = 8;
//stim::image<float> mPb_stack(w,h,theta_n);
//stim::image<float> mPb_theta;
//mPb_theta = func_mPb_theta(lab, theta, w, h);
//mPb_theta.save("data_output/pic_gray_gradient.bmp");
stim::image<float> mPb;
mPb = func_mPb(lab, theta_n, w, h);
}
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