opencv/modules/stitching/blenders.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
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//M*/
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#include "blenders.hpp"
#include "util.hpp"
using namespace std;
using namespace cv;
static const float WEIGHT_EPS = 1e-5f;
Ptr<Blender> Blender::createDefault(int type)
{
if (type == NO)
return new Blender();
if (type == FEATHER)
return new FeatherBlender();
if (type == MULTI_BAND)
return new MultiBandBlender();
CV_Error(CV_StsBadArg, "unsupported blending method");
return NULL;
}
void Blender::prepare(const vector<Point> &corners, const vector<Size> &sizes)
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{
prepare(resultRoi(corners, sizes));
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}
void Blender::prepare(Rect dst_roi)
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{
dst_.create(dst_roi.size(), CV_16SC3);
dst_.setTo(Scalar::all(0));
dst_mask_.create(dst_roi.size(), CV_8U);
dst_mask_.setTo(Scalar::all(0));
dst_roi_ = dst_roi;
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}
void Blender::feed(const Mat &img, const Mat &mask, Point tl)
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{
CV_Assert(img.type() == CV_16SC3);
CV_Assert(mask.type() == CV_8U);
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int dx = tl.x - dst_roi_.x;
int dy = tl.y - dst_roi_.y;
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for (int y = 0; y < img.rows; ++y)
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{
const Point3_<short> *src_row = img.ptr<Point3_<short> >(y);
Point3_<short> *dst_row = dst_.ptr<Point3_<short> >(dy + y);
const uchar *mask_row = mask.ptr<uchar>(y);
uchar *dst_mask_row = dst_mask_.ptr<uchar>(dy + y);
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for (int x = 0; x < img.cols; ++x)
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{
if (mask_row[x])
dst_row[dx + x] = src_row[x];
dst_mask_row[dx + x] |= mask_row[x];
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}
}
}
void Blender::blend(Mat &dst, Mat &dst_mask)
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{
dst_.setTo(Scalar::all(0), dst_mask_ == 0);
dst = dst_;
dst_mask = dst_mask_;
dst_.release();
dst_mask_.release();
}
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void FeatherBlender::prepare(Rect dst_roi)
{
Blender::prepare(dst_roi);
dst_weight_map_.create(dst_roi.size(), CV_32F);
dst_weight_map_.setTo(0);
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}
void FeatherBlender::feed(const Mat &img, const Mat &mask, Point tl)
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{
CV_Assert(img.type() == CV_16SC3);
CV_Assert(mask.type() == CV_8U);
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createWeightMap(mask, sharpness_, weight_map_);
int dx = tl.x - dst_roi_.x;
int dy = tl.y - dst_roi_.y;
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for (int y = 0; y < img.rows; ++y)
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{
const Point3_<short>* src_row = img.ptr<Point3_<short> >(y);
Point3_<short>* dst_row = dst_.ptr<Point3_<short> >(dy + y);
const float* weight_row = weight_map_.ptr<float>(y);
float* dst_weight_row = dst_weight_map_.ptr<float>(dy + y);
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for (int x = 0; x < img.cols; ++x)
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{
dst_row[dx + x].x += static_cast<short>(src_row[x].x * weight_row[x]);
dst_row[dx + x].y += static_cast<short>(src_row[x].y * weight_row[x]);
dst_row[dx + x].z += static_cast<short>(src_row[x].z * weight_row[x]);
dst_weight_row[dx + x] += weight_row[x];
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}
}
}
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void FeatherBlender::blend(Mat &dst, Mat &dst_mask)
{
normalize(dst_weight_map_, dst_);
dst_mask_ = dst_weight_map_ > WEIGHT_EPS;
Blender::blend(dst, dst_mask);
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}
void MultiBandBlender::prepare(Rect dst_roi)
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{
dst_roi_final_ = dst_roi;
// Crop unnecessary bands
double max_len = static_cast<double>(max(dst_roi.width, dst_roi.height));
num_bands_ = min(actual_num_bands_, static_cast<int>(ceil(log(max_len) / log(2.0))));
// Add border to the final image, to ensure sizes are divided by (1 << num_bands_)
dst_roi.width += ((1 << num_bands_) - dst_roi.width % (1 << num_bands_)) % (1 << num_bands_);
dst_roi.height += ((1 << num_bands_) - dst_roi.height % (1 << num_bands_)) % (1 << num_bands_);
Blender::prepare(dst_roi);
dst_pyr_laplace_.resize(num_bands_ + 1);
dst_pyr_laplace_[0] = dst_;
dst_band_weights_.resize(num_bands_ + 1);
dst_band_weights_[0].create(dst_roi.size(), CV_32F);
dst_band_weights_[0].setTo(0);
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for (int i = 1; i <= num_bands_; ++i)
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{
dst_pyr_laplace_[i].create((dst_pyr_laplace_[i - 1].rows + 1) / 2,
(dst_pyr_laplace_[i - 1].cols + 1) / 2, CV_16SC3);
dst_band_weights_[i].create((dst_band_weights_[i - 1].rows + 1) / 2,
(dst_band_weights_[i - 1].cols + 1) / 2, CV_32F);
dst_pyr_laplace_[i].setTo(Scalar::all(0));
dst_band_weights_[i].setTo(0);
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}
}
void MultiBandBlender::feed(const Mat &img, const Mat &mask, Point tl)
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{
CV_Assert(img.type() == CV_16SC3);
CV_Assert(mask.type() == CV_8U);
// Keep source image in memory with small border
int gap = 3 * (1 << num_bands_);
Point tl_new(max(dst_roi_.x, tl.x - gap),
max(dst_roi_.y, tl.y - gap));
Point br_new(min(dst_roi_.br().x, tl.x + img.cols + gap),
min(dst_roi_.br().y, tl.y + img.rows + gap));
// Ensure coordinates of top-left, bootom-right corners are divided by (1 << num_bands_).
// After that scale between layers is exactly 2.
//
// We do it to avoid interpolation problems when keeping sub-images only. There is no such problem when
// image is bordered to have size equal to the final image size, but this is too memory hungry approach.
tl_new.x = dst_roi_.x + (((tl_new.x - dst_roi_.x) >> num_bands_) << num_bands_);
tl_new.y = dst_roi_.y + (((tl_new.y - dst_roi_.y) >> num_bands_) << num_bands_);
int width = br_new.x - tl_new.x;
int height = br_new.y - tl_new.y;
width += ((1 << num_bands_) - width % (1 << num_bands_)) % (1 << num_bands_);
height += ((1 << num_bands_) - height % (1 << num_bands_)) % (1 << num_bands_);
br_new.x = tl_new.x + width;
br_new.y = tl_new.y + height;
int dy = max(br_new.y - dst_roi_.br().y, 0);
int dx = max(br_new.x - dst_roi_.br().x, 0);
tl_new.x -= dx; br_new.x -= dx;
tl_new.y -= dy; br_new.y -= dy;
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int top = tl.y - tl_new.y;
int left = tl.x - tl_new.x;
int bottom = br_new.y - tl.y - img.rows;
int right = br_new.x - tl.x - img.cols;
// Create the source image Laplacian pyramid
vector<Mat> src_pyr_gauss(num_bands_ + 1);
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src_pyr_gauss[0] = img;
copyMakeBorder(img, src_pyr_gauss[0], top, bottom, left, right,
BORDER_REFLECT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(src_pyr_gauss[i], src_pyr_gauss[i + 1]);
vector<Mat> src_pyr_laplace;
createLaplacePyr(src_pyr_gauss, src_pyr_laplace);
src_pyr_gauss.clear();
// Create the weight map Gaussian pyramid
Mat weight_map;
mask.convertTo(weight_map, CV_32F, 1./255.);
vector<Mat> weight_pyr_gauss(num_bands_ + 1);
copyMakeBorder(weight_map, weight_pyr_gauss[0], top, bottom, left, right,
BORDER_CONSTANT);
for (int i = 0; i < num_bands_; ++i)
pyrDown(weight_pyr_gauss[i], weight_pyr_gauss[i + 1]);
int y_tl = tl_new.y - dst_roi_.y;
int y_br = br_new.y - dst_roi_.y;
int x_tl = tl_new.x - dst_roi_.x;
int x_br = br_new.x - dst_roi_.x;
// Add weighted layer of the source image to the final Laplacian pyramid layer
for (int i = 0; i <= num_bands_; ++i)
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{
for (int y = y_tl; y < y_br; ++y)
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{
int y_ = y - y_tl;
const Point3_<short>* src_row = src_pyr_laplace[i].ptr<Point3_<short> >(y_);
Point3_<short>* dst_row = dst_pyr_laplace_[i].ptr<Point3_<short> >(y);
const float* weight_row = weight_pyr_gauss[i].ptr<float>(y_);
float* dst_weight_row = dst_band_weights_[i].ptr<float>(y);
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for (int x = x_tl; x < x_br; ++x)
{
int x_ = x - x_tl;
dst_row[x].x += static_cast<short>(src_row[x_].x * weight_row[x_]);
dst_row[x].y += static_cast<short>(src_row[x_].y * weight_row[x_]);
dst_row[x].z += static_cast<short>(src_row[x_].z * weight_row[x_]);
dst_weight_row[x] += weight_row[x_];
}
}
x_tl /= 2; y_tl /= 2;
x_br /= 2; y_br /= 2;
}
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}
void MultiBandBlender::blend(Mat &dst, Mat &dst_mask)
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{
for (int i = 0; i <= num_bands_; ++i)
normalize(dst_band_weights_[i], dst_pyr_laplace_[i]);
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restoreImageFromLaplacePyr(dst_pyr_laplace_);
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dst_ = dst_pyr_laplace_[0];
dst_ = dst_(Range(0, dst_roi_final_.height), Range(0, dst_roi_final_.width));
dst_mask_ = dst_band_weights_[0] > WEIGHT_EPS;
dst_mask_ = dst_mask_(Range(0, dst_roi_final_.height), Range(0, dst_roi_final_.width));
dst_pyr_laplace_.clear();
dst_band_weights_.clear();
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Blender::blend(dst, dst_mask);
}
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//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
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void normalize(const Mat& weight, Mat& src)
{
CV_Assert(weight.type() == CV_32F);
CV_Assert(src.type() == CV_16SC3);
for (int y = 0; y < src.rows; ++y)
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{
Point3_<short> *row = src.ptr<Point3_<short> >(y);
const float *weight_row = weight.ptr<float>(y);
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for (int x = 0; x < src.cols; ++x)
{
row[x].x = static_cast<short>(row[x].x / (weight_row[x] + WEIGHT_EPS));
row[x].y = static_cast<short>(row[x].y / (weight_row[x] + WEIGHT_EPS));
row[x].z = static_cast<short>(row[x].z / (weight_row[x] + WEIGHT_EPS));
}
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}
}
void createWeightMap(const Mat &mask, float sharpness, Mat &weight)
{
CV_Assert(mask.type() == CV_8U);
distanceTransform(mask, weight, CV_DIST_L1, 3);
threshold(weight * sharpness, weight, 1.f, 1.f, THRESH_TRUNC);
}
void createLaplacePyr(const vector<Mat> &pyr_gauss, vector<Mat> &pyr_laplace)
{
if (pyr_gauss.size() == 0)
return;
pyr_laplace.resize(pyr_gauss.size());
Mat tmp;
for (size_t i = 0; i < pyr_laplace.size() - 1; ++i)
{
pyrUp(pyr_gauss[i + 1], tmp, pyr_gauss[i].size());
subtract(pyr_gauss[i], tmp, pyr_laplace[i]);
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}
pyr_laplace[pyr_laplace.size() - 1] = pyr_gauss[pyr_laplace.size() - 1].clone();
}
void restoreImageFromLaplacePyr(vector<Mat> &pyr)
{
if (pyr.size() == 0)
return;
Mat tmp;
for (size_t i = pyr.size() - 1; i > 0; --i)
{
pyrUp(pyr[i], tmp, pyr[i - 1].size());
add(tmp, pyr[i - 1], pyr[i - 1]);
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}
}