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Minor fixes

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As the opencv's build-bot did not want to compile this revision, I had
to do some changes. In particular,
1) Removed unsigned int vs int comparisons, that were treated as errors
2) Removed unused variables and functions
3) Removed functions without previous declaration
4) Fixed whitespaces
This commit is contained in:
Alex Leontiev
2013-09-01 01:02:06 +08:00
parent ccc71ac190
commit 11fa0651c6
3 changed files with 10 additions and 84 deletions
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86
modules/optim/src/denoise_tvl1.cpp
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@@ -1,5 +1,5 @@
#include "precomp.hpp"
#define ALEX_DEBUG
#undef ALEX_DEBUG
#include "debug.hpp"
#include <vector>
#include <algorithm>
@@ -18,93 +18,24 @@ namespace cv{namespace optim{
float _scale;
};
void solve_TVL1(const Mat& img, Mat& res, double _clambda, int niters)
{
const float L2 = 8.0f, tau = 0.02f, sigma = 1./(L2*tau), theta = 1.f, img_scale = 1.f/255;
float clambda = (float)_clambda, threshold = clambda*tau;
const int workdepth = CV_32F;
int i, x, y, rows=img.rows, cols=img.cols;
Mat X, P = Mat::zeros(rows, cols, CV_MAKETYPE(workdepth, 2));
img.convertTo(X, workdepth, 1./255);
for( i = 0; i < niters; i++ )
{
float currsigma = i == 0 ? 1 + sigma : sigma;
// P_ = P + sigma*nabla(X)
// P(x,y) = P_(x,y)/max(||P(x,y)||,1)
for( y = 0; y < rows; y++ )
{
const float* x_curr = X.ptr<float>(y);
const float* x_next = X.ptr<float>(std::min(y+1, rows-1));
Point2f* p_curr = P.ptr<Point2f>(y);
float dx, dy, m;
for( x = 0; x < cols-1; x++ )
{
dx = (x_curr[x+1] - x_curr[x])*currsigma + p_curr[x].x;
dy = (x_next[x] - x_curr[x])*currsigma + p_curr[x].y;
m = 1.f/std::max(std::sqrt(dx*dx + dy*dy), 1.f);
p_curr[x].x = dx*m;
p_curr[x].y = dy*m;
}
dy = (x_next[x] - x_curr[x])*currsigma + p_curr[x].y;
m = 1.f/std::max(std::abs(dy), 1.f);
p_curr[x].x = 0.f;
p_curr[x].y = dy*m;
}
// X1 = X + tau*(-nablaT(P))
// X2 = X1 + clip(img - X1, -clambda*tau, clambda*tau)
// X = X2 + theta*(X2 - X)
for( y = 0; y < rows; y++ )
{
const uchar* img_curr = img.ptr<uchar>(y);
float* x_curr = X.ptr<float>(y);
const Point2f* p_curr = P.ptr<Point2f>(y);
const Point2f* p_prev = P.ptr<Point2f>(std::max(y - 1, 0));
x = 0;
float x_new = x_curr[x] + tau*(p_curr[x].y - p_prev[x].y);
x_new += std::min(std::max(img_curr[x]*img_scale - x_new, -threshold), threshold);
x_curr[x] = x_new + theta*(x_new - x_curr[x]);
for( x = 1; x < cols; x++ )
{
x_new = x_curr[x] + tau*(p_curr[x].x - p_curr[x-1].x + p_curr[x].y - p_prev[x].y);
x_new += std::min(std::max(img_curr[x]*img_scale - x_new, -threshold), threshold);
x_curr[x] = x_new + theta*(x_new - x_curr[x]);
}
}
}
res.create(X.rows,X.cols,CV_8U);
X.convertTo(res, CV_8U, 255);
}
void denoise_TVL1(const std::vector<Mat>& observations,Mat& result, double lambda, int niters){
CV_Assert(observations.size()>0 && niters>0 && lambda>0);
#if 0
solve_TVL1(observations[0],result,lambda,niters);
return;
#endif
const float L2 = 8.0f, tau = 0.02f, sigma = 1./(L2*tau), theta = 1.f, img_scale = 1.f/255;
float clambda = (float)lambda, threshold = clambda*tau;
const float L2 = 8.0f, tau = 0.02f, sigma = 1./(L2*tau), theta = 1.f;
float clambda = (float)lambda;
float s=0;
const int workdepth = CV_32F;
int i, x, y, rows=observations[0].rows, cols=observations[0].cols,count;
for(i=1;i<observations.size();i++){
for(i=1;i<(int)observations.size();i++){
CV_Assert(observations[i].rows==rows && observations[i].cols==cols);
}
Mat X, P = Mat::zeros(rows, cols, CV_MAKETYPE(workdepth, 2));
observations[0].convertTo(X, workdepth, 1./255);
std::vector< Mat_<float> > Rs(observations.size());
for(count=0;count<Rs.size();count++){
for(count=0;count<(int)Rs.size();count++){
Rs[count]=Mat::zeros(rows,cols,workdepth);
}
@@ -136,7 +67,7 @@ namespace cv{namespace optim{
//Rs = clip(Rs + sigma*(X-imgs), -clambda, clambda)
for(count=0;count<Rs.size();count++){
for(count=0;count<(int)Rs.size();count++){
std::transform<MatIterator_<float>,MatConstIterator_<uchar>,MatIterator_<float>,AddFloatToCharScaled>(
Rs[count].begin(),Rs[count].end(),observations[count].begin<uchar>(),
Rs[count].begin(),AddFloatToCharScaled(-sigma/255.0));
@@ -147,7 +78,6 @@ namespace cv{namespace optim{
for( y = 0; y < rows; y++ )
{
const uchar* img_curr = observations[0].ptr<uchar>(y);
float* x_curr = X.ptr<float>(y);
const Point2f* p_curr = P.ptr<Point2f>(y);
const Point2f* p_prev = P.ptr<Point2f>(std::max(y - 1, 0));
@@ -155,7 +85,7 @@ namespace cv{namespace optim{
// X1 = X + tau*(-nablaT(P))
x = 0;
s=0.0;
for(count=0;count<Rs.size();count++){
for(count=0;count<(int)Rs.size();count++){
s=s+Rs[count](y,x);
}
float x_new = x_curr[x] + tau*(p_curr[x].y - p_prev[x].y)-tau*s;
@@ -166,7 +96,7 @@ namespace cv{namespace optim{
for(x = 1; x < cols; x++ )
{
s=0.0;
for(count=0;count<Rs.size();count++){
for(count=0;count<(int)Rs.size();count++){
s+=Rs[count](y,x);
}
// X1 = X + tau*(-nablaT(P))