//============================================================================= // // fed.cpp // Authors: Pablo F. Alcantarilla (1), Jesus Nuevo (2) // Institutions: Georgia Institute of Technology (1) // TrueVision Solutions (2) // Date: 15/09/2013 // Email: pablofdezalc@gmail.com // // AKAZE Features Copyright 2013, Pablo F. Alcantarilla, Jesus Nuevo // All Rights Reserved // See LICENSE for the license information //============================================================================= /** * @file fed.cpp * @brief Functions for performing Fast Explicit Diffusion and building the * nonlinear scale space * @date Sep 15, 2013 * @author Pablo F. Alcantarilla, Jesus Nuevo * @note This code is derived from FED/FJ library from Grewenig et al., * The FED/FJ library allows solving more advanced problems * Please look at the following papers for more information about FED: * [1] S. Grewenig, J. Weickert, C. Schroers, A. Bruhn. Cyclic Schemes for * PDE-Based Image Analysis. Technical Report No. 327, Department of Mathematics, * Saarland University, Saarbrücken, Germany, March 2013 * [2] S. Grewenig, J. Weickert, A. Bruhn. From box filtering to fast explicit diffusion. * DAGM, 2010 * */ #include "../precomp.hpp" #include "fed.h" using namespace std; //************************************************************************************* //************************************************************************************* /** * @brief This function allocates an array of the least number of time steps such * that a certain stopping time for the whole process can be obtained and fills * it with the respective FED time step sizes for one cycle * The function returns the number of time steps per cycle or 0 on failure * @param T Desired process stopping time * @param M Desired number of cycles * @param tau_max Stability limit for the explicit scheme * @param reordering Reordering flag * @param tau The vector with the dynamic step sizes */ int fed_tau_by_process_time(const float& T, const int& M, const float& tau_max, const bool& reordering, std::vector& tau) { // All cycles have the same fraction of the stopping time return fed_tau_by_cycle_time(T/(float)M,tau_max,reordering,tau); } //************************************************************************************* //************************************************************************************* /** * @brief This function allocates an array of the least number of time steps such * that a certain stopping time for the whole process can be obtained and fills it * it with the respective FED time step sizes for one cycle * The function returns the number of time steps per cycle or 0 on failure * @param t Desired cycle stopping time * @param tau_max Stability limit for the explicit scheme * @param reordering Reordering flag * @param tau The vector with the dynamic step sizes */ int fed_tau_by_cycle_time(const float& t, const float& tau_max, const bool& reordering, std::vector &tau) { int n = 0; // Number of time steps float scale = 0.0; // Ratio of t we search to maximal t // Compute necessary number of time steps n = (int)(ceilf(sqrtf(3.0f*t/tau_max+0.25f)-0.5f-1.0e-8f)+ 0.5f); scale = 3.0f*t/(tau_max*(float)(n*(n+1))); // Call internal FED time step creation routine return fed_tau_internal(n,scale,tau_max,reordering,tau); } //************************************************************************************* //************************************************************************************* /** * @brief This function allocates an array of time steps and fills it with FED * time step sizes * The function returns the number of time steps per cycle or 0 on failure * @param n Number of internal steps * @param scale Ratio of t we search to maximal t * @param tau_max Stability limit for the explicit scheme * @param reordering Reordering flag * @param tau The vector with the dynamic step sizes */ int fed_tau_internal(const int& n, const float& scale, const float& tau_max, const bool& reordering, std::vector &tau) { float c = 0.0, d = 0.0; // Time savers vector tauh; // Helper vector for unsorted taus if (n <= 0) { return 0; } // Allocate memory for the time step size tau = vector(n); if (reordering) { tauh = vector(n); } // Compute time saver c = 1.0f / (4.0f * (float)n + 2.0f); d = scale * tau_max / 2.0f; // Set up originally ordered tau vector for (int k = 0; k < n; ++k) { float h = cosf((float)CV_PI * (2.0f * (float)k + 1.0f) * c); if (reordering) { tauh[k] = d / (h * h); } else { tau[k] = d / (h * h); } } // Permute list of time steps according to chosen reordering function int kappa = 0, prime = 0; if (reordering == true) { // Choose kappa cycle with k = n/2 // This is a heuristic. We can use Leja ordering instead!! kappa = n / 2; // Get modulus for permutation prime = n + 1; while (!fed_is_prime_internal(prime)) { prime++; } // Perform permutation for (int k = 0, l = 0; l < n; ++k, ++l) { int index = 0; while ((index = ((k+1)*kappa) % prime - 1) >= n) { k++; } tau[l] = tauh[index]; } } return n; } //************************************************************************************* //************************************************************************************* /** * @brief This function checks if a number is prime or not * @param number Number to check if it is prime or not * @return true if the number is prime */ bool fed_is_prime_internal(const int& number) { bool is_prime = false; if (number <= 1) { return false; } else if (number == 1 || number == 2 || number == 3 || number == 5 || number == 7) { return true; } else if ((number % 2) == 0 || (number % 3) == 0 || (number % 5) == 0 || (number % 7) == 0) { return false; } else { is_prime = true; int upperLimit = (int)sqrt(1.0f + number); int divisor = 11; while (divisor <= upperLimit ) { if (number % divisor == 0) { is_prime = false; } divisor +=2; } return is_prime; } }