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Merge remote-tracking branch 'origin/2.4' into merge-2.4

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Conflicts:
	.gitignore
	modules/contrib/src/detection_based_tracker.cpp
	modules/core/include/opencv2/core/core.hpp
	modules/core/include/opencv2/core/internal.hpp
	modules/core/src/gpumat.cpp
	modules/core/src/opengl.cpp
	modules/gpu/src/cuda/safe_call.hpp
	modules/highgui/src/cap.cpp
	modules/imgproc/include/opencv2/imgproc/imgproc.hpp
	modules/ocl/doc/image_processing.rst
	modules/ocl/include/opencv2/ocl/ocl.hpp
	modules/ocl/perf/perf_haar.cpp
	modules/ocl/src/haar.cpp
	modules/ocl/src/imgproc.cpp
	modules/ocl/src/kmeans.cpp
	modules/ocl/src/svm.cpp
	modules/ocl/test/test_objdetect.cpp
	samples/ocl/adaptive_bilateral_filter.cpp
This commit is contained in:
Roman Donchenko
2013-11-11 16:55:36 +04:00
parent 469d7eed72 0ac61240c5
commit 4f1aed98de
59 changed files with 961 additions and 755 deletions
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modules/imgproc/doc/filtering.rst
+8 -9
View File
@@ -416,24 +416,23 @@ adaptiveBilateralFilter
-----------------------
Applies the adaptive bilateral filter to an image.
.. ocv:function:: void adaptiveBilateralFilter( InputArray src, OutputArray dst, Size ksize, double sigmaSpace, Point anchor=Point(-1, -1), int borderType=BORDER_DEFAULT )
.. ocv:function:: void adaptiveBilateralFilter( InputArray src, OutputArray dst, Size ksize, double sigmaSpace, double maxSigmaColor = 20.0, Point anchor=Point(-1, -1), int borderType=BORDER_DEFAULT )
.. ocv:pyfunction:: cv2.adaptiveBilateralFilter(src, ksize, sigmaSpace[, dst[, anchor[, borderType]]]) -> dst
:param src: Source 8-bit, 1-channel or 3-channel image.
:param src: The source image
:param dst: Destination image of the same size and type as ``src`` .
:param dst: The destination image; will have the same size and the same type as src
:param ksize: filter kernel size.
:param ksize: The kernel size. This is the neighborhood where the local variance will be calculated, and where pixels will contribute (in a weighted manner).
:param sigmaSpace: Filter sigma in the coordinate space. It has similar meaning with ``sigmaSpace`` in ``bilateralFilter``.
:param sigmaSpace: Filter sigma in the coordinate space. Larger value of the parameter means that farther pixels will influence each other (as long as their colors are close enough; see sigmaColor). Then d>0, it specifies the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace.
:param anchor: anchor point; default value ``Point(-1,-1)`` means that the anchor is at the kernel center. Only default value is supported now.
:param maxSigmaColor: Maximum allowed sigma color (will clamp the value calculated in the ksize neighborhood. Larger value of the parameter means that more dissimilar pixels will influence each other (as long as their colors are close enough; see sigmaColor). Then d>0, it specifies the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace.
:param borderType: border mode used to extrapolate pixels outside of the image.
The function applies adaptive bilateral filtering to the input image. This filter is similar to ``bilateralFilter``, in that dissimilarity from and distance to the center pixel is punished. Instead of using ``sigmaColor``, we employ the variance of pixel values in the neighbourhood.
:param borderType: Pixel extrapolation method.
A main part of our strategy will be to load each raw pixel once, and reuse it to calculate all pixels in the output (filtered) image that need this pixel value. The math of the filter is that of the usual bilateral filter, except that the sigma color is calculated in the neighborhood, and clamped by the optional input value.
blur
modules/imgproc/include/opencv2/imgproc.hpp
+1 -1
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@@ -1067,7 +1067,7 @@ CV_EXPORTS_W void bilateralFilter( InputArray src, OutputArray dst, int d,
//! smooths the image using adaptive bilateral filter
CV_EXPORTS_W void adaptiveBilateralFilter( InputArray src, OutputArray dst, Size ksize,
double sigmaSpace, Point anchor=Point(-1, -1),
double sigmaSpace, double maxSigmaColor = 20.0, Point anchor=Point(-1, -1),
int borderType=BORDER_DEFAULT );
//! smooths the image using the box filter. Each pixel is processed in O(1) time
modules/imgproc/src/smooth.cpp
+67 -18
View File
@@ -2287,15 +2287,24 @@ void cv::bilateralFilter( InputArray _src, OutputArray _dst, int d,
namespace cv
{
#define CALCVAR 1
#define FIXED_WEIGHT 0
#ifndef ABF_CALCVAR
#define ABF_CALCVAR 1
#endif
#ifndef ABF_FIXED_WEIGHT
#define ABF_FIXED_WEIGHT 0
#endif
#ifndef ABF_GAUSSIAN
#define ABF_GAUSSIAN 1
#endif
class adaptiveBilateralFilter_8u_Invoker :
public ParallelLoopBody
{
public:
adaptiveBilateralFilter_8u_Invoker(Mat& _dest, const Mat& _temp, Size _ksize, double _sigma_space, Point _anchor) :
temp(&_temp), dest(&_dest), ksize(_ksize), sigma_space(_sigma_space), anchor(_anchor)
adaptiveBilateralFilter_8u_Invoker(Mat& _dest, const Mat& _temp, Size _ksize, double _sigma_space, double _maxSigmaColor, Point _anchor) :
temp(&_temp), dest(&_dest), ksize(_ksize), sigma_space(_sigma_space), maxSigma_Color(_maxSigmaColor), anchor(_anchor)
{
if( sigma_space <= 0 )
sigma_space = 1;
@@ -2308,7 +2317,11 @@ public:
for(int y=-h; y<=h; y++)
for(int x=-w; x<=w; x++)
{
#if ABF_GAUSSIAN
space_weight[idx++] = (float)exp ( -0.5*(x * x + y * y)/sigma2);
#else
space_weight[idx++] = (float)(sigma2 / (sigma2 + x * x + y * y));
#endif
}
}
virtual void operator()(const Range& range) const
@@ -2344,7 +2357,7 @@ public:
int startLMJ = 0;
int endLMJ = ksize.width - 1;
int howManyAll = (anX *2 +1)*(ksize.width );
#if CALCVAR
#if ABF_CALCVAR
for(int x = startLMJ; x< endLMJ; x++)
{
tptr = temp->ptr(startY + x) +j;
@@ -2356,8 +2369,14 @@ public:
}
}
var = ( (sumValSqr * howManyAll)- sumVal * sumVal ) / ( (float)(howManyAll*howManyAll));
if(var < 0.01)
var = 0.01f;
else if(var > (float)(maxSigma_Color*maxSigma_Color) )
var = (float)(maxSigma_Color*maxSigma_Color) ;
#else
var = 900.0;
var = maxSigmaColor*maxSigmaColor;
#endif
startLMJ = 0;
endLMJ = ksize.width;
@@ -2368,13 +2387,18 @@ public:
tptr = temp->ptr(startY + x) +j;
for(int y=-anX; y<=anX; y++)
{
#if FIXED_WEIGHT
#if ABF_FIXED_WEIGHT
weight = 1.0;
#else
currVal = tptr[cn*(y+anX)];
currWRTCenter = currVal - currValCenter;
weight = var / ( var + (currWRTCenter * currWRTCenter) ) * space_weight[x*ksize.width+y+anX];;
#if ABF_GAUSSIAN
weight = exp ( -0.5f * currWRTCenter * currWRTCenter/var ) * space_weight[x*ksize.width+y+anX];
#else
weight = var / ( var + (currWRTCenter * currWRTCenter) ) * space_weight[x*ksize.width+y+anX];
#endif
#endif
tmpSum += ((float)tptr[cn*(y+anX)] * weight);
totalWeight += weight;
@@ -2409,7 +2433,8 @@ public:
int startLMJ = 0;
int endLMJ = ksize.width - 1;
int howManyAll = (anX *2 +1)*(ksize.width);
#if CALCVAR
#if ABF_CALCVAR
float max_var = (float)( maxSigma_Color*maxSigma_Color);
for(int x = startLMJ; x< endLMJ; x++)
{
tptr = temp->ptr(startY + x) +j;
@@ -2424,11 +2449,27 @@ public:
sumValSqr_r += (currVal_r *currVal_r);
}
}
var_b = ( (sumValSqr_b * howManyAll)- sumVal_b * sumVal_b ) / ( (float)(howManyAll*howManyAll));
var_g = ( (sumValSqr_g * howManyAll)- sumVal_g * sumVal_g ) / ( (float)(howManyAll*howManyAll));
var_r = ( (sumValSqr_r * howManyAll)- sumVal_r * sumVal_r ) / ( (float)(howManyAll*howManyAll));
var_b = ( (sumValSqr_b * howManyAll)- sumVal_b * sumVal_b ) / ( (float)(howManyAll*howManyAll));
var_g = ( (sumValSqr_g * howManyAll)- sumVal_g * sumVal_g ) / ( (float)(howManyAll*howManyAll));
var_r = ( (sumValSqr_r * howManyAll)- sumVal_r * sumVal_r ) / ( (float)(howManyAll*howManyAll));
if(var_b < 0.01)
var_b = 0.01f;
else if(var_b > max_var )
var_b = (float)(max_var) ;
if(var_g < 0.01)
var_g = 0.01f;
else if(var_g > max_var )
var_g = (float)(max_var) ;
if(var_r < 0.01)
var_r = 0.01f;
else if(var_r > max_var )
var_r = (float)(max_var) ;
#else
var_b = 900.0; var_g = 900.0;var_r = 900.0;
var_b = maxSigma_Color*maxSigma_Color; var_g = maxSigma_Color*maxSigma_Color; var_r = maxSigma_Color*maxSigma_Color;
#endif
startLMJ = 0;
endLMJ = ksize.width;
@@ -2439,7 +2480,7 @@ public:
tptr = temp->ptr(startY + x) +j;
for(int y=-anX; y<=anX; y++)
{
#if FIXED_WEIGHT
#if ABF_FIXED_WEIGHT
weight_b = 1.0;
weight_g = 1.0;
weight_r = 1.0;
@@ -2450,9 +2491,16 @@ public:
currWRTCenter_r = currVal_r - currValCenter_r;
float cur_spw = space_weight[x*ksize.width+y+anX];
#if ABF_GAUSSIAN
weight_b = exp( -0.5f * currWRTCenter_b * currWRTCenter_b/ var_b ) * cur_spw;
weight_g = exp( -0.5f * currWRTCenter_g * currWRTCenter_g/ var_g ) * cur_spw;
weight_r = exp( -0.5f * currWRTCenter_r * currWRTCenter_r/ var_r ) * cur_spw;
#else
weight_b = var_b / ( var_b + (currWRTCenter_b * currWRTCenter_b) ) * cur_spw;
weight_g = var_g / ( var_g + (currWRTCenter_g * currWRTCenter_g) ) * cur_spw;
weight_r = var_r / ( var_r + (currWRTCenter_r * currWRTCenter_r) ) * cur_spw;
#endif
#endif
tmpSum_b += ((float)tptr[cn*(y+anX)] * weight_b);
tmpSum_g += ((float)tptr[cn*(y+anX)+1] * weight_g);
@@ -2476,10 +2524,11 @@ private:
Mat *dest;
Size ksize;
double sigma_space;
double maxSigma_Color;
Point anchor;
std::vector<float> space_weight;
};
static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, double sigmaSpace, Point anchor, int borderType )
static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, double sigmaSpace, double maxSigmaColor, Point anchor, int borderType )
{
Size size = src.size();
@@ -2489,12 +2538,12 @@ static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, do
Mat temp;
copyMakeBorder(src, temp, anchor.x, anchor.y, anchor.x, anchor.y, borderType);
adaptiveBilateralFilter_8u_Invoker body(dst, temp, ksize, sigmaSpace, anchor);
adaptiveBilateralFilter_8u_Invoker body(dst, temp, ksize, sigmaSpace, maxSigmaColor, anchor);
parallel_for_(Range(0, size.height), body, dst.total()/(double)(1<<16));
}
}
void cv::adaptiveBilateralFilter( InputArray _src, OutputArray _dst, Size ksize,
double sigmaSpace, Point anchor, int borderType )
double sigmaSpace, double maxSigmaColor, Point anchor, int borderType )
{
Mat src = _src.getMat();
_dst.create(src.size(), src.type());
@@ -2504,7 +2553,7 @@ void cv::adaptiveBilateralFilter( InputArray _src, OutputArray _dst, Size ksize,
anchor = normalizeAnchor(anchor,ksize);
if( src.depth() == CV_8U )
adaptiveBilateralFilter_8u( src, dst, ksize, sigmaSpace, anchor, borderType );
adaptiveBilateralFilter_8u( src, dst, ksize, sigmaSpace, maxSigmaColor, anchor, borderType );
else
CV_Error( CV_StsUnsupportedFormat,
"Adaptive Bilateral filtering is only implemented for 8u images" );