image_processing/gradient_diffusion.cpp

/*******************************************************
 * Copyright (c) 2017, ArrayFire
 * All rights reserved.
 *
 * This file is distributed under 3-clause BSD license.
 * The complete license agreement can be obtained at:
 * http://arrayfire.com/licenses/BSD-3-Clause
 ********************************************************/
 
#include <arrayfire.h>
#include <stdio.h>
#include <af/util.h>
#include <cstdlib>
 
using namespace af;
 
static const unsigned ITERS = 64;
 
array normalize(const array &p_in) {
    float mx = max<float>(p_in);
    float mn = min<float>(p_in);
    return (p_in - mn) / (mx - mn);
}
 
array sobelFilter(const array &p_in) {
    int w = 5;
    if (p_in.dims(0) < 512) w = 3;
    if (p_in.dims(0) > 2048) w = 7;
 
    int h = 5;
    if (p_in.dims(0) < 512) h = 3;
    if (p_in.dims(0) > 2048) h = 7;
 
    array ker    = gaussianKernel(w, h);
    array smooth = convolve(p_in, ker);
 
    for (unsigned i = 1; i < ITERS; ++i) smooth = convolve(smooth, ker);
 
    array Gx, Gy;
    sobel(Gx, Gy, smooth, 3);
 
    return normalize(hypot(Gx, Gy));
}
 
array in, edges, smoothed;
 
void anisotropicSmoothing() {
    smoothed = anisotropicDiffusion(in, 0.125, 0.35f, ITERS);
}
 
int main(int argc, char *argv[]) {
    int device = argc > 1 ? atoi(argv[1]) : 0;
 
    try {
        setDevice(device);
        info();
 
        printf("** ArrayFire Gradient Anisotropic Smoothing Demo **\n");
 
        Window myWindow("Gradient Anisotropic Smoothing");
 
        in = loadImage(ASSETS_DIR "/examples/images/man.jpg", false);
 
        array sEdges = sobelFilter(in);
 
        anisotropicSmoothing();
 
        array Gx, Gy;
        sobel(Gx, Gy, smoothed, 3);
 
        edges = normalize(hypot(Gx, Gy));
 
        while (!myWindow.close()) {
            myWindow.grid(2, 2);
 
            myWindow(0, 0).image(in / 255.0f, "Input Image");
            myWindow(0, 1).image(normalize(smoothed),
                                 "Anisotropically smooted Input");
            myWindow(1, 0).image(normalize(sEdges),
                                 "Gradient Magnitude after gaussian blur t=64");
            myWindow(1, 1).image(normalize(edges),
                                 "Gradient Magnitude after diffusion t=64");
 
            myWindow.show();
        }
 
        printf(
            "\nAnisotropic Diffusion avg runtime for current image in Seconds: "
            "%g\n",
            timeit(anisotropicSmoothing));
 
    } catch (af::exception &e) {
        fprintf(stderr, "%s\n", e.what());
        throw;
    }
 
    return 0;
}