mirror of
https://github.com/OpenCMT/uLib.git
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153 lines
5.2 KiB
C++
153 lines
5.2 KiB
C++
/*//////////////////////////////////////////////////////////////////////////////
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// CMT Cosmic Muon Tomography project //////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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Copyright (c) 2014, Universita' degli Studi di Padova, INFN sez. di Padova
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All rights reserved
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Authors: Andrea Rigoni Garola < andrea.rigoni@pd.infn.it >
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------------------------------------------------------------------
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 3.0 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library.
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//////////////////////////////////////////////////////////////////////////////*/
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#ifndef VOXIMAGEFILTERBILATERAL_HPP
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#define VOXIMAGEFILTERBILATERAL_HPP
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#include <Math/Dense.h>
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#include "Math/VoxImage.h"
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#include "VoxImageFilter.h"
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////////////////////////////////////////////////////////////////////////////////
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///// VOXIMAGE FILTER LINEAR /////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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namespace uLib {
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template <typename VoxelT>
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class VoxFilterAlgorithmBilateral :
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public VoxImageFilter<VoxelT, VoxFilterAlgorithmBilateral<VoxelT> > {
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public:
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typedef VoxImageFilter<VoxelT, VoxFilterAlgorithmBilateral<VoxelT> > BaseClass;
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VoxFilterAlgorithmBilateral(const Vector3i &size) : BaseClass(size) {
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m_sigma = 1;
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}
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float Evaluate(const VoxImage<VoxelT> &buffer, int index)
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{
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const Vector<VoxelT> &vbuf = buffer.ConstData();
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const Vector<VoxelT> &vker = this->m_KernelData.ConstData();
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int vox_size = vbuf.size();
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int ker_size = vker.size();
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int pos;
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float conv = 0, ksum = 0;
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float gamma_smooth;
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for (int ik = 0; ik < ker_size; ++ik) {
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// if (ik==this->m_KernelData.GetCenterData()) continue;
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pos = index + vker[ik].Count - vker[this->m_KernelData.GetCenterData()].Count;
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pos = (pos + vox_size) % vox_size;
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gamma_smooth = compute_gauss( fabs(vbuf[index].Value - vbuf[pos].Value) * 1.E6 );
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conv += vbuf[pos].Value * vker[ik].Value * gamma_smooth;
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ksum += vker[ik].Value * gamma_smooth;
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}
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return conv / ksum;
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}
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inline void SetIntensitySigma(const float s) { m_sigma = s; }
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private:
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inline float compute_gauss(const float x) {
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return 1/(sqrt(2*M_PI)* m_sigma) * exp(-0.5*(x*x)/(m_sigma*m_sigma));
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}
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Scalarf m_sigma;
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};
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template <typename VoxelT>
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class VoxFilterAlgorithmBilateralTrim :
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public VoxImageFilter<VoxelT, VoxFilterAlgorithmBilateralTrim<VoxelT> > {
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typedef std::pair<float,float> FPair;
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struct KernelSortAscending
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{
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bool operator()(const FPair& e1, const FPair& e2)
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{ return e1.second < e2.second; }
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};
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public:
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typedef VoxImageFilter<VoxelT, VoxFilterAlgorithmBilateralTrim<VoxelT> > BaseClass;
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VoxFilterAlgorithmBilateralTrim(const Vector3i &size) : BaseClass(size) {
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m_sigma = 1;
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mAtrim = 0;
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mBtrim = 0;
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}
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float Evaluate(const VoxImage<VoxelT> &buffer, int index)
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{
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const Vector<VoxelT> &vbuf = buffer.ConstData();
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const Vector<VoxelT> &vker = this->m_KernelData.ConstData();
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int img_size = vbuf.size();
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int ker_size = vker.size();
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int pos;
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Vector<FPair> mfh(ker_size);
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for (int i = 0; i < ker_size; ++i)
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mfh[i].first = vker[i].Value; // kernel value in first
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for (int ik = 0; ik < ker_size; ik++) {
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pos = index + vker[ik].Count - vker[this->m_KernelData.GetCenterData()].Count;
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pos = (pos + img_size) % img_size;
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mfh[ik].second = vbuf[pos].Value; // image value in second
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}
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std::sort(mfh.begin(), mfh.end(), KernelSortAscending());
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float conv = 0, ksum = 0;
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float gamma_smooth;
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// for (int ik = 0; ik < mAtrim; ik++)
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// ksum += mfh[ik].first;
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for (int ik = mAtrim; ik < ker_size - mBtrim; ik++) {
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gamma_smooth = compute_gauss( fabs(vbuf[index].Value - mfh[ik].second) * 1.E6 );
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conv += mfh[ik].first * mfh[ik].second * gamma_smooth;
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ksum += mfh[ik].first * gamma_smooth;
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}
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// for (int ik = ker_size - mBtrim; ik < ker_size; ik++)
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// ksum += mfh[ik].first;
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return conv / ksum;
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}
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inline void SetIntensitySigma(const float s) { m_sigma = s; }
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inline void SetABTrim(int a, int b) { mAtrim = a; mBtrim = b; }
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private:
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inline float compute_gauss(const float x) {
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return 1/(sqrt(2*M_PI)* m_sigma) * exp(-0.5*(x*x)/(m_sigma*m_sigma));
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}
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Scalarf m_sigma;
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int mAtrim;
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int mBtrim;
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};
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}
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#endif // VOXIMAGEFILTERBILATERAL_HPP
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