diff --git a/modules/photo/src/fast_nlmeans_denoising_invoker.hpp b/modules/photo/src/fast_nlmeans_denoising_invoker.hpp
index 3e9cc008b..b274c6889 100644
--- a/modules/photo/src/fast_nlmeans_denoising_invoker.hpp
+++ b/modules/photo/src/fast_nlmeans_denoising_invoker.hpp
@@ -51,61 +51,61 @@
using namespace cv;
template <typename T>
-struct FastNlMeansDenoisingInvoker : ParallelLoopBody {
- public:
- FastNlMeansDenoisingInvoker(const Mat& src, Mat& dst,
- int template_window_size, int search_window_size, const float h);
+struct FastNlMeansDenoisingInvoker :
+ public ParallelLoopBody
+{
+public:
+ FastNlMeansDenoisingInvoker(const Mat& src, Mat& dst,
+ int template_window_size, int search_window_size, const float h);
- void operator() (const Range& range) const;
+ void operator() (const Range& range) const;
- private:
- void operator= (const FastNlMeansDenoisingInvoker&);
+private:
+ void operator= (const FastNlMeansDenoisingInvoker&);
- const Mat& src_;
- Mat& dst_;
+ const Mat& src_;
+ Mat& dst_;
- Mat extended_src_;
- int border_size_;
+ Mat extended_src_;
+ int border_size_;
- int template_window_size_;
- int search_window_size_;
+ int template_window_size_;
+ int search_window_size_;
- int template_window_half_size_;
- int search_window_half_size_;
+ int template_window_half_size_;
+ int search_window_half_size_;
- int fixed_point_mult_;
- int almost_template_window_size_sq_bin_shift_;
- std::vector<int> almost_dist2weight_;
+ int fixed_point_mult_;
+ int almost_template_window_size_sq_bin_shift_;
+ std::vector<int> almost_dist2weight_;
- void calcDistSumsForFirstElementInRow(
- int i,
- Array2d<int>& dist_sums,
- Array3d<int>& col_dist_sums,
- Array3d<int>& up_col_dist_sums) const;
+ void calcDistSumsForFirstElementInRow(
+ int i, Array2d<int>& dist_sums,
+ Array3d<int>& col_dist_sums,
+ Array3d<int>& up_col_dist_sums) const;
- void calcDistSumsForElementInFirstRow(
- int i,
- int j,
- int first_col_num,
- Array2d<int>& dist_sums,
- Array3d<int>& col_dist_sums,
- Array3d<int>& up_col_dist_sums) const;
+ void calcDistSumsForElementInFirstRow(
+ int i, int j, int first_col_num,
+ Array2d<int>& dist_sums,
+ Array3d<int>& col_dist_sums,
+ Array3d<int>& up_col_dist_sums) const;
};
inline int getNearestPowerOf2(int value)
{
int p = 0;
- while( 1 << p < value) ++p;
+ while( 1 << p < value)
+ ++p;
return p;
}
template <class T>
FastNlMeansDenoisingInvoker<T>::FastNlMeansDenoisingInvoker(
- const cv::Mat& src,
- cv::Mat& dst,
+ const cv::Mat& src, cv::Mat& dst,
int template_window_size,
int search_window_size,
- const float h) : src_(src), dst_(dst)
+ const float h) :
+ src_(src), dst_(dst)
{
CV_Assert(src.channels() == sizeof(T)); //T is Vec1b or Vec2b or Vec3b
@@ -134,7 +134,8 @@ FastNlMeansDenoisingInvoker<T>::FastNlMeansDenoisingInvoker(
almost_dist2weight_.resize(almost_max_dist);
const double WEIGHT_THRESHOLD = 0.001;
- for (int almost_dist = 0; almost_dist < almost_max_dist; almost_dist++) {
+ for (int almost_dist = 0; almost_dist < almost_max_dist; almost_dist++)
+ {
double dist = almost_dist * almost_dist2actual_dist_multiplier;
int weight = cvRound(fixed_point_mult_ * std::exp(-dist / (h * h * sizeof(T))));
@@ -144,15 +145,15 @@ FastNlMeansDenoisingInvoker<T>::FastNlMeansDenoisingInvoker(
almost_dist2weight_[almost_dist] = weight;
}
CV_Assert(almost_dist2weight_[0] == fixed_point_mult_);
- // additional optimization init end
- if (dst_.empty()) {
+ // additional optimization init end
+ if (dst_.empty())
dst_ = Mat::zeros(src_.size(), src_.type());
- }
}
template <class T>
-void FastNlMeansDenoisingInvoker<T>::operator() (const Range& range) const {
+void FastNlMeansDenoisingInvoker<T>::operator() (const Range& range) const
+{
int row_from = range.start;
int row_to = range.end - 1;
@@ -164,30 +165,36 @@ void FastNlMeansDenoisingInvoker<T>::operator() (const Range& range) const {
int first_col_num = -1;
Array3d<int> up_col_dist_sums(src_.cols, search_window_size_, search_window_size_);
- for (int i = row_from; i <= row_to; i++) {
- for (int j = 0; j < src_.cols; j++) {
+ for (int i = row_from; i <= row_to; i++)
+ {
+ for (int j = 0; j < src_.cols; j++)
+ {
int search_window_y = i - search_window_half_size_;
int search_window_x = j - search_window_half_size_;
// calc dist_sums
- if (j == 0) {
+ if (j == 0)
+ {
calcDistSumsForFirstElementInRow(i, dist_sums, col_dist_sums, up_col_dist_sums);
first_col_num = 0;
- } else { // calc cur dist_sums using previous dist_sums
- if (i == row_from) {
+ }
+ else
+ {
+ // calc cur dist_sums using previous dist_sums
+ if (i == row_from)
+ {
calcDistSumsForElementInFirstRow(i, j, first_col_num,
dist_sums, col_dist_sums, up_col_dist_sums);
- } else {
+ }
+ else
+ {
int ay = border_size_ + i;
int ax = border_size_ + j + template_window_half_size_;
- int start_by =
- border_size_ + i - search_window_half_size_;
-
- int start_bx =
- border_size_ + j - search_window_half_size_ + template_window_half_size_;
+ int start_by = border_size_ + i - search_window_half_size_;
+ int start_bx = border_size_ + j - search_window_half_size_ + template_window_half_size_;
T a_up = extended_src_.at<T>(ay - template_window_half_size_ - 1, ax);
T a_down = extended_src_.at<T>(ay + template_window_half_size_, ax);
@@ -195,20 +202,18 @@ void FastNlMeansDenoisingInvoker<T>::operator() (const Range& range) const {
// copy class member to local variable for optimization
int search_window_size = search_window_size_;
- for (int y = 0; y < search_window_size; y++) {
+ for (int y = 0; y < search_window_size; y++)
+ {
int* dist_sums_row = dist_sums.row_ptr(y);
int* col_dist_sums_row = col_dist_sums.row_ptr(first_col_num,y);
-
int* up_col_dist_sums_row = up_col_dist_sums.row_ptr(j, y);
- const T* b_up_ptr =
- extended_src_.ptr<T>(start_by - template_window_half_size_ - 1 + y);
+ const T* b_up_ptr = extended_src_.ptr<T>(start_by - template_window_half_size_ - 1 + y);
+ const T* b_down_ptr = extended_src_.ptr<T>(start_by + template_window_half_size_ + y);
- const T* b_down_ptr =
- extended_src_.ptr<T>(start_by + template_window_half_size_ + y);
-
- for (int x = 0; x < search_window_size; x++) {
+ for (int x = 0; x < search_window_size; x++)
+ {
dist_sums_row[x] -= col_dist_sums_row[x];
col_dist_sums_row[x] =
@@ -233,14 +238,15 @@ void FastNlMeansDenoisingInvoker<T>::operator() (const Range& range) const {
int weights_sum = 0;
int estimation[3];
- for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++) {
+ for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++)
estimation[channel_num] = 0;
- }
- for (int y = 0; y < search_window_size_; y++) {
+ for (int y = 0; y < search_window_size_; y++)
+ {
const T* cur_row_ptr = extended_src_.ptr<T>(border_size_ + search_window_y + y);
int* dist_sums_row = dist_sums.row_ptr(y);
- for (int x = 0; x < search_window_size_; x++) {
+ for (int x = 0; x < search_window_size_; x++)
+ {
int almostAvgDist =
dist_sums_row[x] >> almost_template_window_size_sq_bin_shift_;
@@ -269,18 +275,19 @@ inline void FastNlMeansDenoisingInvoker<T>::calcDistSumsForFirstElementInRow(
{
int j = 0;
- for (int y = 0; y < search_window_size_; y++) {
- for (int x = 0; x < search_window_size_; x++) {
+ for (int y = 0; y < search_window_size_; y++)
+ for (int x = 0; x < search_window_size_; x++)
+ {
dist_sums[y][x] = 0;
- for (int tx = 0; tx < template_window_size_; tx++) {
+ for (int tx = 0; tx < template_window_size_; tx++)
col_dist_sums[tx][y][x] = 0;
- }
int start_y = i + y - search_window_half_size_;
int start_x = j + x - search_window_half_size_;
- for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++) {
- for (int tx = -template_window_half_size_; tx <= template_window_half_size_; tx++) {
+ for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++)
+ for (int tx = -template_window_half_size_; tx <= template_window_half_size_; tx++)
+ {
int dist = calcDist<T>(extended_src_,
border_size_ + i + ty, border_size_ + j + tx,
border_size_ + start_y + ty, border_size_ + start_x + tx);
@@ -288,11 +295,9 @@ inline void FastNlMeansDenoisingInvoker<T>::calcDistSumsForFirstElementInRow(
dist_sums[y][x] += dist;
col_dist_sums[tx + template_window_half_size_][y][x] += dist;
}
- }
up_col_dist_sums[j][y][x] = col_dist_sums[template_window_size_ - 1][y][x];
}
- }
}
template <class T>
@@ -312,23 +317,21 @@ inline void FastNlMeansDenoisingInvoker<T>::calcDistSumsForElementInFirstRow(
int new_last_col_num = first_col_num;
- for (int y = 0; y < search_window_size_; y++) {
- for (int x = 0; x < search_window_size_; x++) {
+ for (int y = 0; y < search_window_size_; y++)
+ for (int x = 0; x < search_window_size_; x++)
+ {
dist_sums[y][x] -= col_dist_sums[first_col_num][y][x];
col_dist_sums[new_last_col_num][y][x] = 0;
int by = start_by + y;
int bx = start_bx + x;
- for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++) {
+ for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++)
col_dist_sums[new_last_col_num][y][x] +=
calcDist<T>(extended_src_, ay + ty, ax, by + ty, bx);
- }
dist_sums[y][x] += col_dist_sums[new_last_col_num][y][x];
-
up_col_dist_sums[j][y][x] = col_dist_sums[new_last_col_num][y][x];
}
- }
}
#endif
diff --git a/modules/photo/src/fast_nlmeans_denoising_invoker_commons.hpp b/modules/photo/src/fast_nlmeans_denoising_invoker_commons.hpp
index 978f3170c..3e8f4c498 100644
--- a/modules/photo/src/fast_nlmeans_denoising_invoker_commons.hpp
+++ b/modules/photo/src/fast_nlmeans_denoising_invoker_commons.hpp
@@ -46,29 +46,35 @@ using namespace cv;
template <typename T> static inline int calcDist(const T a, const T b);
-template <> inline int calcDist(const uchar a, const uchar b) {
+template <> inline int calcDist(const uchar a, const uchar b)
+{
return (a-b) * (a-b);
}
-template <> inline int calcDist(const Vec2b a, const Vec2b b) {
+template <> inline int calcDist(const Vec2b a, const Vec2b b)
+{
return (a[0]-b[0])*(a[0]-b[0]) + (a[1]-b[1])*(a[1]-b[1]);
}
-template <> inline int calcDist(const Vec3b a, const Vec3b b) {
+template <> inline int calcDist(const Vec3b a, const Vec3b b)
+{
return (a[0]-b[0])*(a[0]-b[0]) + (a[1]-b[1])*(a[1]-b[1]) + (a[2]-b[2])*(a[2]-b[2]);
}
-template <typename T> static inline int calcDist(const Mat& m, int i1, int j1, int i2, int j2) {
+template <typename T> static inline int calcDist(const Mat& m, int i1, int j1, int i2, int j2)
+{
const T a = m.at<T>(i1, j1);
const T b = m.at<T>(i2, j2);
return calcDist<T>(a,b);
}
-template <typename T> static inline int calcUpDownDist(T a_up, T a_down, T b_up, T b_down) {
+template <typename T> static inline int calcUpDownDist(T a_up, T a_down, T b_up, T b_down)
+{
return calcDist(a_down,b_down) - calcDist(a_up, b_up);
}
-template <> inline int calcUpDownDist(uchar a_up, uchar a_down, uchar b_up, uchar b_down) {
+template <> inline int calcUpDownDist(uchar a_up, uchar a_down, uchar b_up, uchar b_down)
+{
int A = a_down - b_down;
int B = a_up - b_up;
return (A-B)*(A+B);
@@ -76,16 +82,20 @@ template <> inline int calcUpDownDist(uchar a_up, uchar a_down, uchar b_up, uch
template <typename T> static inline void incWithWeight(int* estimation, int weight, T p);
-template <> inline void incWithWeight(int* estimation, int weight, uchar p) {
+template <> inline void incWithWeight(int* estimation, int weight, uchar p)
+{
+
estimation[0] += weight * p;
}
-template <> inline void incWithWeight(int* estimation, int weight, Vec2b p) {
+template <> inline void incWithWeight(int* estimation, int weight, Vec2b p)
+{
estimation[0] += weight * p[0];
estimation[1] += weight * p[1];
}
-template <> inline void incWithWeight(int* estimation, int weight, Vec3b p) {
+template <> inline void incWithWeight(int* estimation, int weight, Vec3b p)
+{
estimation[0] += weight * p[0];
estimation[1] += weight * p[1];
estimation[2] += weight * p[2];
@@ -93,18 +103,21 @@ template <> inline void incWithWeight(int* estimation, int weight, Vec3b p) {
template <typename T> static inline T saturateCastFromArray(int* estimation);
-template <> inline uchar saturateCastFromArray(int* estimation) {
+template <> inline uchar saturateCastFromArray(int* estimation)
+{
return saturate_cast<uchar>(estimation[0]);
}
-template <> inline Vec2b saturateCastFromArray(int* estimation) {
+template <> inline Vec2b saturateCastFromArray(int* estimation)
+{
Vec2b res;
res[0] = saturate_cast<uchar>(estimation[0]);
res[1] = saturate_cast<uchar>(estimation[1]);
return res;
}
-template <> inline Vec3b saturateCastFromArray(int* estimation) {
+template <> inline Vec3b saturateCastFromArray(int* estimation)
+{
Vec3b res;
res[0] = saturate_cast<uchar>(estimation[0]);
res[1] = saturate_cast<uchar>(estimation[1]);
diff --git a/modules/photo/src/fast_nlmeans_multi_denoising_invoker.hpp b/modules/photo/src/fast_nlmeans_multi_denoising_invoker.hpp
index e2351a23c..191a67127 100644
--- a/modules/photo/src/fast_nlmeans_multi_denoising_invoker.hpp
+++ b/modules/photo/src/fast_nlmeans_multi_denoising_invoker.hpp
@@ -51,51 +51,47 @@
using namespace cv;
template <typename T>
-struct FastNlMeansMultiDenoisingInvoker : ParallelLoopBody {
- public:
- FastNlMeansMultiDenoisingInvoker(
- const std::vector<Mat>& srcImgs, int imgToDenoiseIndex, int temporalWindowSize,
- Mat& dst, int template_window_size, int search_window_size, const float h);
+struct FastNlMeansMultiDenoisingInvoker :
+ ParallelLoopBody
+{
+public:
+ FastNlMeansMultiDenoisingInvoker(const std::vector<Mat>& srcImgs, int imgToDenoiseIndex,
+ int temporalWindowSize, Mat& dst, int template_window_size,
+ int search_window_size, const float h);
- void operator() (const Range& range) const;
+ void operator() (const Range& range) const;
- private:
- void operator= (const FastNlMeansMultiDenoisingInvoker&);
+private:
+ void operator= (const FastNlMeansMultiDenoisingInvoker&);
- int rows_;
- int cols_;
+ int rows_;
+ int cols_;
- Mat& dst_;
+ Mat& dst_;
- std::vector<Mat> extended_srcs_;
- Mat main_extended_src_;
- int border_size_;
+ std::vector<Mat> extended_srcs_;
+ Mat main_extended_src_;
+ int border_size_;
- int template_window_size_;
- int search_window_size_;
- int temporal_window_size_;
+ int template_window_size_;
+ int search_window_size_;
+ int temporal_window_size_;
- int template_window_half_size_;
- int search_window_half_size_;
- int temporal_window_half_size_;
+ int template_window_half_size_;
+ int search_window_half_size_;
+ int temporal_window_half_size_;
- int fixed_point_mult_;
- int almost_template_window_size_sq_bin_shift;
- std::vector<int> almost_dist2weight;
+ int fixed_point_mult_;
+ int almost_template_window_size_sq_bin_shift;
+ std::vector<int> almost_dist2weight;
- void calcDistSumsForFirstElementInRow(
- int i,
- Array3d<int>& dist_sums,
- Array4d<int>& col_dist_sums,
- Array4d<int>& up_col_dist_sums) const;
+ void calcDistSumsForFirstElementInRow(int i, Array3d<int>& dist_sums,
+ Array4d<int>& col_dist_sums,
+ Array4d<int>& up_col_dist_sums) const;
- void calcDistSumsForElementInFirstRow(
- int i,
- int j,
- int first_col_num,
- Array3d<int>& dist_sums,
- Array4d<int>& col_dist_sums,
- Array4d<int>& up_col_dist_sums) const;
+ void calcDistSumsForElementInFirstRow(int i, int j, int first_col_num,
+ Array3d<int>& dist_sums, Array4d<int>& col_dist_sums,
+ Array4d<int>& up_col_dist_sums) const;
};
template <class T>
@@ -106,7 +102,8 @@ FastNlMeansMultiDenoisingInvoker<T>::FastNlMeansMultiDenoisingInvoker(
cv::Mat& dst,
int template_window_size,
int search_window_size,
- const float h) : dst_(dst), extended_srcs_(srcImgs.size())
+ const float h) :
+ dst_(dst), extended_srcs_(srcImgs.size())
{
CV_Assert(srcImgs.size() > 0);
CV_Assert(srcImgs[0].channels() == sizeof(T));
@@ -123,85 +120,84 @@ FastNlMeansMultiDenoisingInvoker<T>::FastNlMeansMultiDenoisingInvoker(
temporal_window_size_ = temporal_window_half_size_ * 2 + 1;
border_size_ = search_window_half_size_ + template_window_half_size_;
- for (int i = 0; i < temporal_window_size_; i++) {
- copyMakeBorder(
- srcImgs[imgToDenoiseIndex - temporal_window_half_size_ + i], extended_srcs_[i],
+ for (int i = 0; i < temporal_window_size_; i++)
+ copyMakeBorder(srcImgs[imgToDenoiseIndex - temporal_window_half_size_ + i], extended_srcs_[i],
border_size_, border_size_, border_size_, border_size_, cv::BORDER_DEFAULT);
- }
+
main_extended_src_ = extended_srcs_[temporal_window_half_size_];
-
- const int max_estimate_sum_value =
- temporal_window_size_ * search_window_size_ * search_window_size_ * 255;
-
+ const int max_estimate_sum_value = temporal_window_size_ * search_window_size_ * search_window_size_ * 255;
fixed_point_mult_ = std::numeric_limits<int>::max() / max_estimate_sum_value;
// precalc weight for every possible l2 dist between blocks
// additional optimization of precalced weights to replace division(averaging) by binary shift
int template_window_size_sq = template_window_size_ * template_window_size_;
almost_template_window_size_sq_bin_shift = 0;
- while (1 << almost_template_window_size_sq_bin_shift < template_window_size_sq) {
+ while (1 << almost_template_window_size_sq_bin_shift < template_window_size_sq)
almost_template_window_size_sq_bin_shift++;
- }
int almost_template_window_size_sq = 1 << almost_template_window_size_sq_bin_shift;
- double almost_dist2actual_dist_multiplier =
- ((double) almost_template_window_size_sq) / template_window_size_sq;
+ double almost_dist2actual_dist_multiplier = (double) almost_template_window_size_sq / template_window_size_sq;
int max_dist = 255 * 255 * sizeof(T);
int almost_max_dist = (int) (max_dist / almost_dist2actual_dist_multiplier + 1);
almost_dist2weight.resize(almost_max_dist);
const double WEIGHT_THRESHOLD = 0.001;
- for (int almost_dist = 0; almost_dist < almost_max_dist; almost_dist++) {
+ for (int almost_dist = 0; almost_dist < almost_max_dist; almost_dist++)
+ {
double dist = almost_dist * almost_dist2actual_dist_multiplier;
int weight = cvRound(fixed_point_mult_ * std::exp(-dist / (h * h * sizeof(T))));
- if (weight < WEIGHT_THRESHOLD * fixed_point_mult_) {
+ if (weight < WEIGHT_THRESHOLD * fixed_point_mult_)
weight = 0;
- }
almost_dist2weight[almost_dist] = weight;
}
CV_Assert(almost_dist2weight[0] == fixed_point_mult_);
- // additional optimization init end
- if (dst_.empty()) {
+ // additional optimization init end
+ if (dst_.empty())
dst_ = Mat::zeros(srcImgs[0].size(), srcImgs[0].type());
- }
}
template <class T>
-void FastNlMeansMultiDenoisingInvoker<T>::operator() (const Range& range) const {
+void FastNlMeansMultiDenoisingInvoker<T>::operator() (const Range& range) const
+{
int row_from = range.start;
int row_to = range.end - 1;
Array3d<int> dist_sums(temporal_window_size_, search_window_size_, search_window_size_);
// for lazy calc optimization
- Array4d<int> col_dist_sums(
- template_window_size_, temporal_window_size_, search_window_size_, search_window_size_);
+ Array4d<int> col_dist_sums(template_window_size_, temporal_window_size_, search_window_size_, search_window_size_);
int first_col_num = -1;
+ Array4d<int> up_col_dist_sums(cols_, temporal_window_size_, search_window_size_, search_window_size_);
- Array4d<int> up_col_dist_sums(
- cols_, temporal_window_size_, search_window_size_, search_window_size_);
-
- for (int i = row_from; i <= row_to; i++) {
- for (int j = 0; j < cols_; j++) {
+ for (int i = row_from; i <= row_to; i++)
+ {
+ for (int j = 0; j < cols_; j++)
+ {
int search_window_y = i - search_window_half_size_;
int search_window_x = j - search_window_half_size_;
// calc dist_sums
- if (j == 0) {
+ if (j == 0)
+ {
calcDistSumsForFirstElementInRow(i, dist_sums, col_dist_sums, up_col_dist_sums);
first_col_num = 0;
-
- } else { // calc cur dist_sums using previous dist_sums
- if (i == row_from) {
+ }
+ else
+ {
+ // calc cur dist_sums using previous dist_sums
+ if (i == row_from)
+ {
calcDistSumsForElementInFirstRow(i, j, first_col_num,
dist_sums, col_dist_sums, up_col_dist_sums);
- } else {
+ }
+ else
+ {
int ay = border_size_ + i;
int ax = border_size_ + j + template_window_half_size_;
@@ -217,36 +213,31 @@ void FastNlMeansMultiDenoisingInvoker<T>::operator() (const Range& range) const
// copy class member to local variable for optimization
int search_window_size = search_window_size_;
- for (int d = 0; d < temporal_window_size_; d++) {
+ for (int d = 0; d < temporal_window_size_; d++)
+ {
Mat cur_extended_src = extended_srcs_[d];
Array2d<int> cur_dist_sums = dist_sums[d];
Array2d<int> cur_col_dist_sums = col_dist_sums[first_col_num][d];
Array2d<int> cur_up_col_dist_sums = up_col_dist_sums[j][d];
- for (int y = 0; y < search_window_size; y++) {
+ for (int y = 0; y < search_window_size; y++)
+ {
int* dist_sums_row = cur_dist_sums.row_ptr(y);
int* col_dist_sums_row = cur_col_dist_sums.row_ptr(y);
-
int* up_col_dist_sums_row = cur_up_col_dist_sums.row_ptr(y);
- const T* b_up_ptr =
- cur_extended_src.ptr<T>(start_by - template_window_half_size_ - 1 + y);
- const T* b_down_ptr =
- cur_extended_src.ptr<T>(start_by + template_window_half_size_ + y);
+ const T* b_up_ptr = cur_extended_src.ptr<T>(start_by - template_window_half_size_ - 1 + y);
+ const T* b_down_ptr = cur_extended_src.ptr<T>(start_by + template_window_half_size_ + y);
- for (int x = 0; x < search_window_size; x++) {
+ for (int x = 0; x < search_window_size; x++)
+ {
dist_sums_row[x] -= col_dist_sums_row[x];
col_dist_sums_row[x] = up_col_dist_sums_row[x] +
- calcUpDownDist(
- a_up, a_down,
- b_up_ptr[start_bx + x], b_down_ptr[start_bx + x]
- );
+ calcUpDownDist(a_up, a_down, b_up_ptr[start_bx + x], b_down_ptr[start_bx + x]);
dist_sums_row[x] += col_dist_sums_row[x];
-
up_col_dist_sums_row[x] = col_dist_sums_row[x];
-
}
}
}
@@ -259,19 +250,21 @@ void FastNlMeansMultiDenoisingInvoker<T>::operator() (const Range& range) const
int weights_sum = 0;
int estimation[3];
- for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++) {
+ for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++)
estimation[channel_num] = 0;
- }
- for (int d = 0; d < temporal_window_size_; d++) {
+
+ for (int d = 0; d < temporal_window_size_; d++)
+ {
const Mat& esrc_d = extended_srcs_[d];
- for (int y = 0; y < search_window_size_; y++) {
+ for (int y = 0; y < search_window_size_; y++)
+ {
const T* cur_row_ptr = esrc_d.ptr<T>(border_size_ + search_window_y + y);
int* dist_sums_row = dist_sums.row_ptr(d, y);
- for (int x = 0; x < search_window_size_; x++) {
- int almostAvgDist =
- dist_sums_row[x] >> almost_template_window_size_sq_bin_shift;
+ for (int x = 0; x < search_window_size_; x++)
+ {
+ int almostAvgDist = dist_sums_row[x] >> almost_template_window_size_sq_bin_shift;
int weight = almost_dist2weight[almostAvgDist];
weights_sum += weight;
@@ -293,21 +286,19 @@ void FastNlMeansMultiDenoisingInvoker<T>::operator() (const Range& range) const
template <class T>
inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForFirstElementInRow(
- int i,
- Array3d<int>& dist_sums,
- Array4d<int>& col_dist_sums,
- Array4d<int>& up_col_dist_sums) const
+ int i, Array3d<int>& dist_sums, Array4d<int>& col_dist_sums, Array4d<int>& up_col_dist_sums) const
{
int j = 0;
- for (int d = 0; d < temporal_window_size_; d++) {
+ for (int d = 0; d < temporal_window_size_; d++)
+ {
Mat cur_extended_src = extended_srcs_[d];
- for (int y = 0; y < search_window_size_; y++) {
- for (int x = 0; x < search_window_size_; x++) {
+ for (int y = 0; y < search_window_size_; y++)
+ for (int x = 0; x < search_window_size_; x++)
+ {
dist_sums[d][y][x] = 0;
- for (int tx = 0; tx < template_window_size_; tx++) {
+ for (int tx = 0; tx < template_window_size_; tx++)
col_dist_sums[tx][d][y][x] = 0;
- }
int start_y = i + y - search_window_half_size_;
int start_x = j + x - search_window_half_size_;
@@ -315,14 +306,13 @@ inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForFirstElementInRo
int* dist_sums_ptr = &dist_sums[d][y][x];
int* col_dist_sums_ptr = &col_dist_sums[0][d][y][x];
int col_dist_sums_step = col_dist_sums.step_size(0);
- for (int tx = -template_window_half_size_; tx <= template_window_half_size_; tx++) {
- for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++) {
+ for (int tx = -template_window_half_size_; tx <= template_window_half_size_; tx++)
+ {
+ for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++)
+ {
int dist = calcDist<T>(
- main_extended_src_.at<T>(
- border_size_ + i + ty, border_size_ + j + tx),
- cur_extended_src.at<T>(
- border_size_ + start_y + ty, border_size_ + start_x + tx)
- );
+ main_extended_src_.at<T>(border_size_ + i + ty, border_size_ + j + tx),
+ cur_extended_src.at<T>(border_size_ + start_y + ty, border_size_ + start_x + tx));
*dist_sums_ptr += dist;
*col_dist_sums_ptr += dist;
@@ -332,18 +322,13 @@ inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForFirstElementInRo
up_col_dist_sums[j][d][y][x] = col_dist_sums[template_window_size_ - 1][d][y][x];
}
- }
}
}
template <class T>
inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForElementInFirstRow(
- int i,
- int j,
- int first_col_num,
- Array3d<int>& dist_sums,
- Array4d<int>& col_dist_sums,
- Array4d<int>& up_col_dist_sums) const
+ int i, int j, int first_col_num, Array3d<int>& dist_sums,
+ Array4d<int>& col_dist_sums, Array4d<int>& up_col_dist_sums) const
{
int ay = border_size_ + i;
int ax = border_size_ + j + template_window_half_size_;
@@ -353,10 +338,12 @@ inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForElementInFirstRo
int new_last_col_num = first_col_num;
- for (int d = 0; d < temporal_window_size_; d++) {
+ for (int d = 0; d < temporal_window_size_; d++)
+ {
Mat cur_extended_src = extended_srcs_[d];
- for (int y = 0; y < search_window_size_; y++) {
- for (int x = 0; x < search_window_size_; x++) {
+ for (int y = 0; y < search_window_size_; y++)
+ for (int x = 0; x < search_window_size_; x++)
+ {
dist_sums[d][y][x] -= col_dist_sums[first_col_num][d][y][x];
col_dist_sums[new_last_col_num][d][y][x] = 0;
@@ -364,19 +351,17 @@ inline void FastNlMeansMultiDenoisingInvoker<T>::calcDistSumsForElementInFirstRo
int bx = start_bx + x;
int* col_dist_sums_ptr = &col_dist_sums[new_last_col_num][d][y][x];
- for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++) {
- *col_dist_sums_ptr +=
- calcDist<T>(
- main_extended_src_.at<T>(ay + ty, ax),
- cur_extended_src.at<T>(by + ty, bx)
- );
+ for (int ty = -template_window_half_size_; ty <= template_window_half_size_; ty++)
+ {
+ *col_dist_sums_ptr += calcDist<T>(
+ main_extended_src_.at<T>(ay + ty, ax),
+ cur_extended_src.at<T>(by + ty, bx));
}
dist_sums[d][y][x] += col_dist_sums[new_last_col_num][d][y][x];
up_col_dist_sums[j][d][y][x] = col_dist_sums[new_last_col_num][d][y][x];
}
- }
}
}