Chiebot-Mirror
/
opencv_contrib
mirror of https://github.com/opencv/opencv_contrib.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

modified stereo for better results

Browse Source
pull/326/head
Muresan Mircea Paul 9 years ago
parent 1ae4d2a874
commit 12b530c6b1
3 changed files with 46 additions and 53 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 63
      modules/stereo/src/matching.hpp
  2. 10
      modules/stereo/src/stereo_binary_bm.cpp
  3. 26
      modules/stereo/src/stereo_binary_sgbm.cpp

63
modules/stereo/src/matching.hpp
Unescape View File

@ -281,20 +281,20 @@ namespace cv
}
};
//!median 1x9 paralelized filter
template <typename T>
class Median1x9:public ParallelLoopBody
{
private:
uint8_t *original;
uint8_t *filtered;
int height, width,_stride;
T *original;
T *filtered;
int height, width;
public:
Median1x9(const Mat &originalImage, Mat &filteredImage)
{
original = originalImage.data;
filtered = filteredImage.data;
original = (T *)originalImage.data;
filtered = (T *)filteredImage.data;
height = originalImage.rows;
width = originalImage.cols;
_stride = (int)originalImage.step;
}
void operator()(const cv::Range &r) const{
for (int m = r.start; m <= r.end; m++)
@ -302,39 +302,39 @@ namespace cv
for (int n = 4; n < width - 4; ++n)
{
int k = 0;
uint8_t window[9];
T window[9];
for (int i = n - 4; i <= n + 4; ++i)
window[k++] = original[m * _stride + i];
window[k++] = original[m * width + i];
for (int j = 0; j < 5; ++j)
{
int min = j;
for (int l = j + 1; l < 9; ++l)
if (window[l] < window[min])
min = l;
const uint8_t temp = window[j];
const T temp = window[j];
window[j] = window[min];
window[min] = temp;
}
filtered[m * _stride + n] = window[4];
filtered[m * width + n] = window[4];
}
}
}
};
//!median 9x1 paralelized filter
template <typename T>
class Median9x1:public ParallelLoopBody
{
private:
uint8_t *original;
uint8_t *filtered;
int height, width, _stride;
T *original;
T *filtered;
int height, width;
public:
Median9x1(const Mat &originalImage, Mat &filteredImage)
{
original = originalImage.data;
filtered = filteredImage.data;
original = (T *)originalImage.data;
filtered = (T *)filteredImage.data;
height = originalImage.rows;
width = originalImage.cols;
_stride = (int)originalImage.step;
}
void operator()(const Range &r) const{
for (int n = r.start; n <= r.end; ++n)
@ -342,20 +342,20 @@ namespace cv
for (int m = 4; m < height - 4; ++m)
{
int k = 0;
uint8_t window[9];
T window[9];
for (int i = m - 4; i <= m + 4; ++i)
window[k++] = original[i * _stride + n];
window[k++] = original[i * width + n];
for (int j = 0; j < 5; j++)
{
int min = j;
for (int l = j + 1; l < 9; ++l)
if (window[l] < window[min])
min = l;
const uint8_t temp = window[j];
const T temp = window[j];
window[j] = window[min];
window[min] = temp;
}
filtered[m * _stride + n] = window[4];
filtered[m * width + n] = window[4];
}
}
}
@ -471,6 +471,7 @@ namespace cv
parallel_for_(cv::Range(win + 1,height - win - 1), agregateCost(partialSums,windowSize,maxDisp,cost));
}
//!remove small regions that have an area smaller than t, we fill the region with the average of the good pixels around it
template <typename T>
void smallRegionRemoval(const Mat &currentMap, int t, Mat &out)
{
CV_Assert(currentMap.cols == out.cols);
@ -480,11 +481,11 @@ namespace cv
int *specklePointX = (int *)speckleX.data;
int *specklePointY = (int *)speckleY.data;
memset(pus, 0, previous_size * sizeof(pus[0]));
uint8_t *map = currentMap.data;
uint8_t *outputMap = out.data;
T *map = (T *)currentMap.data;
T *outputMap = (T *)out.data;
int height = currentMap.rows;
int width = currentMap.cols;
uint8_t k = 1;
T k = 1;
int st, dr;
int di[] = { -1, -1, -1, 0, 1, 1, 1, 0 },
dj[] = { -1, 0, 1, 1, 1, 0, -1, -1 };
@ -502,8 +503,8 @@ namespace cv
}
else if (map[iw + j] == 0)
{
int nr = 1;
int avg = 0;
T nr = 1;
T avg = 0;
speckle_size = dr;
specklePointX[dr] = i;
specklePointY[dr] = j;
@ -520,7 +521,7 @@ namespace cv
if (ii + di[d] >= 0 && ii + di[d] < height && jj + dj[d] >= 0 && jj + dj[d] < width &&
pus[(ii + di[d]) * width + jj + dj[d]] == 0)
{
int val = map[(ii + di[d]) * width + jj + dj[d]];
T val = map[(ii + di[d]) * width + jj + dj[d]];
if (val == 0)
{
map[(ii + di[d]) * width + jj + dj[d]] = k;
@ -529,7 +530,7 @@ namespace cv
dr++;
pus[(ii + di[d]) * width + jj + dj[d]] = 1;
}//this means that my point is a good point to be used in computing the final filling value
else if (val > 2 && val < 250)
else if (val >= 1 && val < 250)
{
avg += val;
nr++;
@ -540,7 +541,7 @@ namespace cv
}//if hole size is smaller than a specified threshold we fill the respective hole with the average of the good neighbours
if (st - speckle_size <= t)
{
uint8_t fillValue = (uint8_t)(avg / nr);
T fillValue = (T)(avg / nr);
while (speckle_size < st)
{
int ii = specklePointX[speckle_size];
@ -573,18 +574,20 @@ namespace cv
public:
//!a median filter of 1x9 and 9x1
//!1x9 median filter
template<typename T>
void Median1x9Filter(const Mat &originalImage, Mat &filteredImage)
{
CV_Assert(originalImage.rows == filteredImage.rows);
CV_Assert(originalImage.cols == filteredImage.cols);
parallel_for_(Range(1,originalImage.rows - 2), Median1x9(originalImage,filteredImage));
parallel_for_(Range(1,originalImage.rows - 2), Median1x9<T>(originalImage,filteredImage));
}
//!9x1 median filter
template<typename T>
void Median9x1Filter(const Mat &originalImage, Mat &filteredImage)
{
CV_Assert(originalImage.cols == filteredImage.cols);
CV_Assert(originalImage.cols == filteredImage.cols);
parallel_for_(Range(1,originalImage.cols - 2), Median9x1(originalImage,filteredImage));
parallel_for_(Range(1,originalImage.cols - 2), Median9x1<T>(originalImage,filteredImage));
}
//!constructor for the matching class
//!maxDisp - represents the maximum disparity

10
modules/stereo/src/stereo_binary_bm.cpp
Unescape View File

@ -324,7 +324,6 @@ namespace cv
int width = left0.cols;
int height = left0.rows;
if(previous_size != width * height)
{
previous_size = width * height;
@ -341,6 +340,8 @@ namespace cv
preFilteredImg0.create(left0.size(), CV_8U);
preFilteredImg1.create(left0.size(), CV_8U);
aux.create(height,width,CV_8UC1);
}
Mat left = preFilteredImg0, right = preFilteredImg1;
@ -405,12 +406,12 @@ namespace cv
costGathering(hammingDistance, partialSumsLR);
blockAgregation(partialSumsLR, params.agregationWindowSize, agregatedHammingLRCost);
dispartyMapFormation(agregatedHammingLRCost, disp0, 3);
Median1x9Filter(disp0, disp0);
Median9x1Filter(disp0,disp0);
Median1x9Filter<uint8_t>(disp0, aux);
Median9x1Filter<uint8_t>(aux,disp0);
if(params.regionRemoval == CV_SPECKLE_REMOVAL_AVG_ALGORITHM)
{
smallRegionRemoval(disp0,params.speckleWindowSize,disp0);
smallRegionRemoval<uint8_t>(disp0,params.speckleWindowSize,disp0);
}
else if(params.regionRemoval == CV_SPECKLE_REMOVAL_ALGORITHM)
{
@ -511,6 +512,7 @@ namespace cv
Mat hammingDistance;
Mat partialSumsLR;
Mat agregatedHammingLRCost;
Mat aux;
static const char* name_;
};

26
modules/stereo/src/stereo_binary_sgbm.cpp
Unescape View File

@ -701,32 +701,20 @@ namespace cv
speckleY.create(height,width,CV_32SC4);
puss.create(height,width,CV_32SC4);
}
double minVal; double maxVal;
Mat imgDisparity8U2;
imgDisparity8U2.create(height,width,CV_8UC1);
Mat aux;
aux.create(height,width,CV_8UC1);
minMaxLoc(disp, &minVal, &maxVal);
disp.convertTo(imgDisparity8U2, CV_8UC1, 255 / (maxVal - minVal));
Median1x9Filter(imgDisparity8U2, aux);
Median9x1Filter(aux,imgDisparity8U2);
smallRegionRemoval(imgDisparity8U2,params.speckleWindowSize,imgDisparity8U2);
imgDisparity8U2.convertTo(disp, CV_16S);
aux.create(height,width,CV_16S);
Median1x9Filter<short>(disp, aux);
Median9x1Filter<short>(aux,disp);
smallRegionRemoval<short>(disp, params.speckleWindowSize, disp);
}
else if(params.regionRemoval == CV_SPECKLE_REMOVAL_ALGORITHM)
{
int width = left.cols;
int height = left.rows;
double minVal; double maxVal;
Mat imgDisparity8U2;
imgDisparity8U2.create(height,width,CV_8UC1);
Mat aux;
aux.create(height,width,CV_8UC1);
minMaxLoc(disp, &minVal, &maxVal);
disp.convertTo(imgDisparity8U2, CV_8UC1, 255 / (maxVal - minVal));
Median1x9Filter(imgDisparity8U2, aux);
Median9x1Filter(aux,imgDisparity8U2);
imgDisparity8U2.convertTo(disp, CV_16S);
aux.create(height,width,CV_16S);
Median1x9Filter<short>(disp, aux);
Median9x1Filter<short>(aux,disp);
if( params.speckleWindowSize > 0 )
filterSpeckles(disp, (params.minDisparity - 1) * StereoMatcher::DISP_SCALE, params.speckleWindowSize,
StereoMatcher::DISP_SCALE * params.speckleRange, buffer);

Write Preview
Loading…
Cancel
Save