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edge preserve filters added and windows warning removed

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update1
pull/1447/head
siddharth 12 years ago
parent 1ed0e44090
commit ae9b4003ae
2 changed files with 524 additions and 0 deletions
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  1. 34
      modules/photo/src/npr.cpp
  2. 490
      modules/photo/src/npr.hpp

34
modules/photo/src/npr.cpp
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#include "precomp.hpp"
#include "opencv2/photo.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <stdlib.h>
#include "npr.hpp"
using namespace std;
using namespace cv;
void cv::edgepreservefilter(InputArray _src, OutputArray _dst, int flags, float sigma_s, float sigma_r)
{
Mat I = _src.getMat();
_dst.create(I.size(), CV_8UC3);
Mat dst = _dst.getMat();
int h = I.size().height;
int w = I.size().width;
Mat res = Mat(h,w,CV_32FC3);
dst.convertTo(res,CV_32FC3,1.0/255.0);
Domain_Filter obj;
Mat img = Mat(I.size(),CV_32FC3);
I.convertTo(img,CV_32FC3,1.0/255.0);
obj.filter(img, res, sigma_s, sigma_r, flags);
convertScaleAbs(res, dst, 255,0);
}

490
modules/photo/src/npr.hpp
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#include "precomp.hpp"
#include "opencv2/photo.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <stdlib.h>
#include <limits>
#include "math.h"
using namespace std;
using namespace cv;
double myinf = std::numeric_limits<double>::infinity();
class Domain_Filter
{
public:
Mat ct_H, ct_V, horiz, vert, O, O_t, lower_idx, upper_idx;
void init(const Mat &img, int flags, float sigma_s, float sigma_r);
void getGradientx( const Mat &img, Mat &gx);
void getGradienty( const Mat &img, Mat &gy);
void diffx(const Mat &img, Mat &temp);
void diffy(const Mat &img, Mat &temp);
void compute_boxfilter(Mat &output, Mat &hz, Mat &psketch, float radius);
void compute_Rfilter(Mat &O, Mat &horiz, float sigma_h);
void compute_NCfilter(Mat &O, Mat &horiz, Mat &psketch, float radius);
void filter(const Mat &img, Mat &res, float sigma_s, float sigma_r, int flags);
};
void Domain_Filter::diffx(const Mat &img, Mat &temp)
{
int channel = img.channels();
for(int i = 0; i < img.size().height; i++)
for(int j = 0; j < img.size().width-1; j++)
{
for(int c =0; c < channel; c++)
{
temp.at<float>(i,j*channel+c) =
img.at<float>(i,(j+1)*channel+c) - img.at<float>(i,j*channel+c);
}
}
}
void Domain_Filter::diffy(const Mat &img, Mat &temp)
{
int channel = img.channels();
for(int i = 0; i < img.size().height-1; i++)
for(int j = 0; j < img.size().width; j++)
{
for(int c =0; c < channel; c++)
{
temp.at<float>(i,j*channel+c) =
img.at<float>((i+1),j*channel+c) - img.at<float>(i,j*channel+c);
}
}
}
void Domain_Filter::getGradientx( const Mat &img, Mat &gx)
{
int w = img.cols;
int h = img.rows;
int channel = img.channels();
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;++c)
{
gx.at<float>(i,j*channel+c) =
img.at<float>(i,(j+1)*channel+c) - img.at<float>(i,j*channel+c);
}
}
void Domain_Filter::getGradienty( const Mat &img, Mat &gy)
{
int w = img.cols;
int h = img.rows;
int channel = img.channels();
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;++c)
{
gy.at<float>(i,j*channel+c) =
img.at<float>(i+1,j*channel+c) - img.at<float>(i,j*channel+c);
}
}
void Domain_Filter::compute_Rfilter(Mat &output, Mat &hz, float sigma_h)
{
float a;
int h = output.rows;
int w = output.cols;
int channel = output.channels();
a = exp(-sqrt(2) / sigma_h);
Mat temp = Mat(h,w,CV_32FC3);
for(int i =0; i < h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;c++)
temp.at<float>(i,j*channel+c) = output.at<float>(i,j*channel+c);
Mat V = Mat(h,w,CV_32FC1);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
V.at<float>(i,j) = pow(a,hz.at<float>(i,j));
for(int i=0; i<h; i++)
{
for(int j =1; j < w; j++)
{
for(int c = 0; c<channel; c++)
{
temp.at<float>(i,j*channel+c) = temp.at<float>(i,j*channel+c) +
(temp.at<float>(i,(j-1)*channel+c) - temp.at<float>(i,j*channel+c)) * V.at<float>(i,j);
}
}
}
for(int i=0; i<h; i++)
{
for(int j =w-2; j >= 0; j--)
{
for(int c = 0; c<channel; c++)
{
temp.at<float>(i,j*channel+c) = temp.at<float>(i,j*channel+c) +
(temp.at<float>(i,(j+1)*channel+c) - temp.at<float>(i,j*channel+c))*V.at<float>(i,j+1);
}
}
}
for(int i =0; i < h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;c++)
output.at<float>(i,j*channel+c) = temp.at<float>(i,j*channel+c);
temp.release();
V.release();
}
void Domain_Filter::compute_boxfilter(Mat &output, Mat &hz, Mat &psketch, float radius)
{
int h = output.rows;
int w = output.cols;
Mat lower_pos = Mat(h,w,CV_32FC1);
Mat upper_pos = Mat(h,w,CV_32FC1);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
{
lower_pos.at<float>(i,j) = hz.at<float>(i,j) - radius;
upper_pos.at<float>(i,j) = hz.at<float>(i,j) + radius;
}
lower_idx = Mat::zeros(h,w,CV_32FC1);
upper_idx = Mat::zeros(h,w,CV_32FC1);
Mat domain_row = Mat::zeros(1,w+1,CV_32FC1);
for(int i=0;i<h;i++)
{
for(int j=0;j<w;j++)
domain_row.at<float>(0,j) = hz.at<float>(i,j);
domain_row.at<float>(0,w) = myinf;
Mat lower_pos_row = Mat::zeros(1,w,CV_32FC1);
Mat upper_pos_row = Mat::zeros(1,w,CV_32FC1);
for(int j=0;j<w;j++)
{
lower_pos_row.at<float>(0,j) = lower_pos.at<float>(i,j);
upper_pos_row.at<float>(0,j) = upper_pos.at<float>(i,j);
}
Mat temp_lower_idx = Mat::zeros(1,w,CV_32FC1);
Mat temp_upper_idx = Mat::zeros(1,w,CV_32FC1);
for(int j=0;j<w;j++)
{
if(domain_row.at<float>(0,j) > lower_pos_row.at<float>(0,0))
{
temp_lower_idx.at<float>(0,0) = j;
break;
}
}
for(int j=0;j<w;j++)
{
if(domain_row.at<float>(0,j) > upper_pos_row.at<float>(0,0))
{
temp_upper_idx.at<float>(0,0) = j;
break;
}
}
int temp = 0;
for(int j=1;j<w;j++)
{
int count=0;
for(int k=temp_lower_idx.at<float>(0,j-1);k<w+1;k++)
{
if(domain_row.at<float>(0,k) > lower_pos_row.at<float>(0,j))
{
temp = count;
break;
}
count++;
}
temp_lower_idx.at<float>(0,j) = temp_lower_idx.at<float>(0,j-1) + temp;
count = 0;
for(int k=temp_upper_idx.at<float>(0,j-1);k<w+1;k++)
{
if(domain_row.at<float>(0,k) > upper_pos_row.at<float>(0,j))
{
temp = count;
break;
}
count++;
}
temp_upper_idx.at<float>(0,j) = temp_upper_idx.at<float>(0,j-1) + temp;
}
for(int j=0;j<w;j++)
{
lower_idx.at<float>(i,j) = temp_lower_idx.at<float>(0,j) + 1;
upper_idx.at<float>(i,j) = temp_upper_idx.at<float>(0,j) + 1;
}
lower_pos_row.release();
upper_pos_row.release();
temp_lower_idx.release();
temp_upper_idx.release();
}
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
psketch.at<float>(i,j) = upper_idx.at<float>(i,j) - lower_idx.at<float>(i,j);
}
void Domain_Filter::compute_NCfilter(Mat &output, Mat &hz, Mat &psketch, float radius)
{
int h = output.rows;
int w = output.cols;
int channel = output.channels();
compute_boxfilter(output,hz,psketch,radius);
Mat box_filter = Mat::zeros(h,w+1,CV_32FC3);
for(int i = 0; i < h; i++)
{
box_filter.at<float>(i,1*channel+0) = output.at<float>(i,0*channel+0);
box_filter.at<float>(i,1*channel+1) = output.at<float>(i,0*channel+1);
box_filter.at<float>(i,1*channel+2) = output.at<float>(i,0*channel+2);
for(int j = 2; j < w+1; j++)
{
for(int c=0;c<channel;c++)
box_filter.at<float>(i,j*channel+c) = output.at<float>(i,(j-1)*channel+c) + box_filter.at<float>(i,(j-1)*channel+c);
}
}
Mat indices = Mat::zeros(h,w,CV_32FC1);
Mat final = Mat::zeros(h,w,CV_32FC3);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
indices.at<float>(i,j) = i+1;
Mat a = Mat::zeros(h,w,CV_32FC1);
Mat b = Mat::zeros(h,w,CV_32FC1);
for(int c=0;c<channel;c++)
{
Mat flag = Mat::ones(h,w,CV_32FC1);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
flag.at<float>(i,j) = (c+1)*flag.at<float>(i,j);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
{
a.at<float>(i,j) = (flag.at<float>(i,j) - 1) * h * (w+1) + (lower_idx.at<float>(i,j) - 1) * h + indices.at<float>(i,j);
b.at<float>(i,j) = (flag.at<float>(i,j) - 1) * h * (w+1) + (upper_idx.at<float>(i,j) - 1) * h + indices.at<float>(i,j);
}
int p,q,r,rem;
int p1,q1,r1,rem1;
for(int i=0;i<h;i++)
{
for(int j=0;j<w;j++)
{
r = b.at<float>(i,j)/(h*(w+1));
rem = b.at<float>(i,j) - r*h*(w+1);
q = rem/h;
p = rem - q*h;
if(q==0)
{
p=h;
q=w;
r=r-1;
}
if(p==0)
{
p=h;
q=q-1;
}
r1 = a.at<float>(i,j)/(h*(w+1));
rem1 = a.at<float>(i,j) - r1*h*(w+1);
q1 = rem1/h;
p1 = rem1 - q1*h;
if(p1==0)
{
p1=h;
q1=q1-1;
}
final.at<float>(i,j*channel+2-c) = (box_filter.at<float>(p-1,q*channel+(2-r)) - box_filter.at<float>(p1-1,q1*channel+(2-r1)))
/(upper_idx.at<float>(i,j) - lower_idx.at<float>(i,j));
}
}
}
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;c++)
output.at<float>(i,j*channel+c) = final.at<float>(i,j*channel+c);
}
void Domain_Filter::init(const Mat &img, int flags, float sigma_s, float sigma_r)
{
int h = img.size().height;
int w = img.size().width;
int channel = img.channels();
//////////////////////////////////// horizontal and vertical partial derivatives /////////////////////////////////
Mat derivx = Mat::zeros(h,w-1,CV_32FC3);
Mat derivy = Mat::zeros(h-1,w,CV_32FC3);
diffx(img,derivx);
diffy(img,derivy);
Mat distx = Mat::zeros(h,w,CV_32FC1);
Mat disty = Mat::zeros(h,w,CV_32FC1);
//////////////////////// Compute the l1-norm distance of neighbor pixels ////////////////////////////////////////////////
for(int i = 0; i < h; i++)
for(int j = 0,k=1; j < w-1; j++,k++)
for(int c = 0; c < channel; c++)
{
distx.at<float>(i,k) =
distx.at<float>(i,k) + abs(derivx.at<float>(i,j*channel+c));
}
for(int i = 0,k=1; i < h-1; i++,k++)
for(int j = 0; j < w; j++)
for(int c = 0; c < channel; c++)
{
disty.at<float>(k,j) =
disty.at<float>(k,j) + abs(derivy.at<float>(i,j*channel+c));
}
////////////////////// Compute the derivatives of the horizontal and vertical domain transforms. /////////////////////////////
horiz = Mat(h,w,CV_32FC1);
vert = Mat(h,w,CV_32FC1);
Mat final = Mat(h,w,CV_32FC3);
for(int i = 0; i < h; i++)
for(int j = 0; j < w; j++)
{
horiz.at<float>(i,j) = (float) 1.0 + (sigma_s/sigma_r) * distx.at<float>(i,j);
vert.at<float>(i,j) = (float) 1.0 + (sigma_s/sigma_r) * disty.at<float>(i,j);
}
O = Mat(h,w,CV_32FC3);
for(int i =0;i<h;i++)
for(int j =0;j<w;j++)
for(int c=0;c<channel;c++)
O.at<float>(i,j*channel+c) = img.at<float>(i,j*channel+c);
O_t = Mat(w,h,CV_32FC3);
if(flags == 2)
{
ct_H = Mat(h,w,CV_32FC1);
ct_V = Mat(h,w,CV_32FC1);
for(int i = 0; i < h; i++)
{
ct_H.at<float>(i,0) = horiz.at<float>(i,0);
for(int j = 1; j < w; j++)
{
ct_H.at<float>(i,j) = horiz.at<float>(i,j) + ct_H.at<float>(i,j-1);
}
}
for(int j = 0; j < w; j++)
{
ct_V.at<float>(0,j) = vert.at<float>(0,j);
for(int i = 1; i < h; i++)
{
ct_V.at<float>(i,j) = vert.at<float>(i,j) + ct_V.at<float>(i-1,j);
}
}
}
}
void Domain_Filter::filter(const Mat &img, Mat &res, float sigma_s = 60, float sigma_r = 0.4, int flags = 1)
{
int no_of_iter = 3;
int h = img.size().height;
int w = img.size().width;
float sigma_h = sigma_s;
init(img,flags,sigma_s,sigma_r);
if(flags == 1)
{
Mat vert_t = vert.t();
for(int i=0;i<no_of_iter;i++)
{
sigma_h = sigma_s * sqrt(3) * pow(2.0,(no_of_iter - (i+1))) / sqrt(pow(4.0,no_of_iter) -1);
compute_Rfilter(O, horiz, sigma_h);
O_t = O.t();
compute_Rfilter(O_t, vert_t, sigma_h);
O = O_t.t();
}
}
else if(flags == 2)
{
Mat vert_t = ct_V.t();
Mat temp = Mat(h,w,CV_32FC1);
Mat temp1 = Mat(w,h,CV_32FC1);
float radius;
for(int i=0;i<no_of_iter;i++)
{
sigma_h = sigma_s * sqrt(3) * pow(2.0,(no_of_iter - (i+1))) / sqrt(pow(4.0,no_of_iter) -1);
radius = sqrt(3) * sigma_h;
compute_NCfilter(O, ct_H, temp,radius);
O_t = O.t();
compute_NCfilter(O_t, vert_t, temp1, radius);
O = O_t.t();
}
}
res = O.clone();
}
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