eef14f76dd
Moved debayer and preprocessing parameters to class ProcParams for every single image. Added tab RAW for changing those parameters. Progress bar shows only load step (work to do)
95 lines
2.3 KiB
C++
95 lines
2.3 KiB
C++
/*
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* This file is part of RawTherapee.
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*
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* RawTherapee is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* RawTherapee 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
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with RawTherapee. If not, see <http://www.gnu.org/licenses/>.
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*
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* 2010 Ilya Popov <ilia_popov@rambler.ru>
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*/
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#ifndef WAVELET_DEC_H_INCLUDED
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#define WAVELET_DEC_H_INCLUDED
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#include <cstddef>
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#include "wavelet_level.h"
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namespace rtengine {
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class wavelet_decomposition
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{
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public:
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typedef float internal_type;
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private:
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static const int maxlevels = 8;
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int nlevels;
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size_t m_w, m_h;
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size_t m_w1, m_h1;
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wavelet_level<internal_type> * m_c[maxlevels];
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public:
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template<typename E>
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wavelet_decomposition(E ** src, size_t w, size_t h);
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~wavelet_decomposition();
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template<typename E, typename L>
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void reconstruct(E ** dst, const int * c, L & limiter);
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};
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//////////////////////////////////////////////////////////////////////////////
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template<typename E>
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wavelet_decomposition::wavelet_decomposition(E ** src, size_t w, size_t h)
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: nlevels(0), m_w(w), m_h(h), m_w1(0), m_h1(0)
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{
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m_w1 = w;
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m_h1 = h;
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m_c[0] = new wavelet_level<internal_type>(src, m_w1, m_h1);
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nlevels = 1;
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while(nlevels < maxlevels)
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{
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m_c[nlevels] = new wavelet_level<internal_type>(m_c[nlevels - 1]->lowfreq(), m_c[nlevels-1]->lfw(), m_c[nlevels-1]->lfh());
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nlevels ++;
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}
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}
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template<typename E, typename L>
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void wavelet_decomposition::reconstruct(E ** dst, const int * c, L & l)
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{
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noop<internal_type> n;
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for(int level = nlevels - 1; level > 0; level--)
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{
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int alpha = 1024 + 10 * c[level];
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m_c[level]->reconstruct(m_c[level-1]->lowfreq(), alpha, n);
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}
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int alpha = 1024 + 10 * c[0];
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m_c[0]->reconstruct(dst, alpha, l);
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}
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};
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#endif
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