add stackblur for imgproc.

pull/20379/head
Zihao Mu 3 years ago
parent 2619099fe5
commit 2918071a3e
  1. 16
      modules/imgproc/include/opencv2/imgproc.hpp
  2. 48
      modules/imgproc/perf/perf_blur.cpp
  3. 1261
      modules/imgproc/src/stackblur.cpp
  4. 313
      modules/imgproc/test/test_stackblur.cpp

@ -1620,6 +1620,22 @@ CV_EXPORTS_W void blur( InputArray src, OutputArray dst,
Size ksize, Point anchor = Point(-1,-1),
int borderType = BORDER_DEFAULT );
/** @brief Blurs an image using the StackBlur.
The function applies and StackBlur to an image.
StackBlur can generate similar results as Gaussian blur, and the time does not increase as the kernel size increases.
It creates a kind of moving stack of colors whilst scanning through the image. Thereby it just has to add one new block of color to the right side
of the stack and remove the leftmost color. The remaining colors on the topmost layer of the stack are either added on or reduced by one,
depending on if they are on the right or on the left side of the stack.
Described here: http://underdestruction.com/2004/02/25/stackblur-2004.
Stack Blur Algorithm by Mario Klingemann <mario@quasimondo.com>
@param src input image. The number of channels can be arbitrary, but the depth should be one of
CV_8U, CV_16U, CV_16S or CV_32F.
@param dst output image of the same size and type as src.
@param ksize stack-blurring kernel size. The ksize.width and ksize.height can differ but they both must be
positive and odd.
*/
CV_EXPORTS_W void stackBlur(InputArray src, OutputArray dst, Size ksize);
/** @brief Convolves an image with the kernel.
The function applies an arbitrary linear filter to an image. In-place operation is supported. When

@ -253,4 +253,52 @@ PERF_TEST_P(Size_MatType, BlendLinear,
SANITY_CHECK_NOTHING();
}
///////////// Stackblur ////////////////////////
PERF_TEST_P(Size_MatType, stackblur3x3,
testing::Combine(
testing::Values(sz720p, sz1080p, sz2160p),
testing::Values(CV_8UC1, CV_8UC4, CV_16UC1, CV_16SC1, CV_32FC1)
)
)
{
Size size = get<0>(GetParam());
int type = get<1>(GetParam());
double eps = 1e-3;
eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : eps;
Mat src(size, type);
Mat dst(size, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() stackBlur(src, dst, Size(3,3));
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(Size_MatType, stackblur101x101,
testing::Combine(
testing::Values(sz720p, sz1080p, sz2160p),
testing::Values(CV_8UC1, CV_8UC4, CV_16UC1, CV_16SC1, CV_32FC1)
)
)
{
Size size = get<0>(GetParam());
int type = get<1>(GetParam());
double eps = 1e-3;
eps = CV_MAT_DEPTH(type) <= CV_32S ? 1 : eps;
Mat src(size, type);
Mat dst(size, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() stackBlur(src, dst, Size(101,101));
SANITY_CHECK_NOTHING();
}
} // namespace

File diff suppressed because it is too large Load Diff

@ -0,0 +1,313 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
/*
StackBlur - a fast almost Gaussian Blur
Theory: http://underdestruction.com/2004/02/25/stackblur-2004
The code has been borrowed from (https://github.com/flozz/StackBlur).
Below is the original copyright
*/
/*
Copyright (c) 2010 Mario Klingemann
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
template<typename T>
void _stackblurRef(const Mat& src, Mat& dst, Size ksize)
{
CV_Assert(!src.empty());
CV_Assert(ksize.width > 0 && ksize.height > 0 && ksize.height % 2 == 1 && ksize.width % 2 == 1);
dst.create(src.size(), src.type());
const int CN = src.channels();
int rowsImg = src.rows;
int colsImg = src.cols;
int wm = colsImg - 1;
int radiusW = ksize.width / 2;
int stackLenW = ksize.width;
const float mulW = 1.0f / (((float )radiusW + 1.0f) * ((float )radiusW + 1.0f));
// Horizontal direction
std::vector<T> stack(stackLenW * CN);
for (int row = 0; row < rowsImg; row++)
{
std::vector<float> sum(CN, 0);
std::vector<float> sumIn(CN, 0);
std::vector<float> sumOut(CN, 0);
const T* srcPtr = src.ptr<T>(row);
for (int i = 0; i <= radiusW; i++)
{
for (int ci = 0; ci < CN; ci++)
{
T tmp = *(srcPtr + ci);
stack[i * CN + ci] = tmp;
sum[ci] += tmp * (i + 1);
sumOut[ci] += tmp;
}
}
for (int i = 1; i <= radiusW; i++)
{
if (i <= wm) srcPtr += CN;
for(int ci = 0; ci < CN; ci++)
{
T tmp = *(srcPtr + ci);
stack[(i + radiusW) * CN + ci] = tmp;
sum[ci] += tmp * (radiusW + 1 - i);
sumIn[ci] += tmp;
}
}
int sp = radiusW;
int xp = radiusW ;
if (xp > wm) xp = wm;
T* dstPtr = dst.ptr<T>(row);
srcPtr = src.ptr<T>(row) + xp * CN;
int stackStart= 0;
for (int i = 0; i < colsImg; i++)
{
stackStart = sp + stackLenW - radiusW;
if (stackStart >= stackLenW) stackStart -= stackLenW;
for(int ci = 0; ci < CN; ci++)
{
*(dstPtr + ci) = cv::saturate_cast<T>(sum[ci] * mulW);
sum[ci] -= sumOut[ci];
sumOut[ci] -= stack[stackStart*CN + ci];
}
const T* srcNew = srcPtr;
if(xp < wm)
srcNew += CN;
for (int ci = 0; ci < CN; ci++)
{
stack[stackStart * CN + ci] = *(srcNew + ci);
sumIn[ci] += *(srcNew + ci);
sum[ci] += sumIn[ci];
}
int sp1 = sp + 1;
sp1 &= -(sp1 < stackLenW);
for(int ci = 0; ci < CN; ci++)
{
T tmp = stack[sp1*CN + ci];
sumOut[ci] += tmp;
sumIn[ci] -= tmp;
}
dstPtr += CN;
if (xp < wm)
{
xp++;
srcPtr += CN;
}
++sp;
if (sp >= stackLenW) sp = 0;
}
}
// Vertical direction
int hm = rowsImg - 1;
int widthElem = colsImg * CN;
int radiusH = ksize.height / 2;
int stackLenH = ksize.height;
const float mulH = 1.0f / (((float )radiusH + 1.0f) * ((float )radiusH + 1.0f));
stack.resize(stackLenH, 0);
for (int col = 0; col < widthElem; col++)
{
const T* srcPtr =dst.ptr<T>() + col;
float sum0 = 0;
float sumIn0 = 0;
float sumOut0 = 0;
for (int i = 0; i <= radiusH; i++)
{
T tmp = (T)(*srcPtr);
stack[i] = tmp;
sum0 += tmp * (i + 1);
sumOut0 += tmp;
}
for (int i = 1; i <= radiusH; i++)
{
if (i <= hm) srcPtr += widthElem;
T tmp = (T)(*srcPtr);
stack[i + radiusH] = tmp;
sum0 += tmp * (radiusH - i + 1);
sumIn0 += tmp;
}
int sp = radiusH;
int yp = radiusH;
if (yp > hm) yp = hm;
T* dstPtr = dst.ptr<T>() + col;
srcPtr = dst.ptr<T>(yp) + col;
const T* srcNew;
int stackStart = 0;
for (int i = 0; i < rowsImg; i++)
{
stackStart = sp + stackLenH - radiusH;
if (stackStart >= stackLenH) stackStart -= stackLenH;
*(dstPtr) = saturate_cast<T>(sum0 * mulH);
sum0 -= sumOut0;
sumOut0 -= stack[stackStart];
srcNew = srcPtr;
if (yp < hm)
srcNew += widthElem;
stack[stackStart] = *(srcNew);
sumIn0 += *(srcNew);
sum0 += sumIn0;
int sp1 = sp + 1;
sp1 &= -(sp1 < stackLenH);
sumOut0 += stack[sp1];
sumIn0 -= stack[sp1];
dstPtr += widthElem;
if (yp < hm)
{
yp++;
srcPtr += widthElem;
}
++sp;
if (sp >= stackLenH) sp = 0;
}
}
}
void stackBlurRef(const Mat& img, Mat& dst, Size ksize)
{
if(img.depth() == CV_8U)
_stackblurRef<uchar>(img, dst, ksize);
else if (img.depth() == CV_16S)
_stackblurRef<short>(img, dst, ksize);
else if (img.depth() == CV_16U)
_stackblurRef<ushort>(img, dst, ksize);
else if (img.depth() == CV_32F)
_stackblurRef<float>(img, dst, ksize);
else
CV_Error_( CV_StsNotImplemented,
("Unsupported Mat type in stackBlurRef, "
"the supported formats are: CV_8U, CV_16U, CV_16S and CV_32F."));
}
std::vector<Size> kernelSizeVec = {
Size(3, 3),
Size(5, 5),
Size(101, 101),
Size(3, 9)
};
typedef testing::TestWithParam<tuple<int, int, int> > StackBlur;
TEST_P (StackBlur, regression)
{
Mat img_ = imread(findDataFile("shared/fruits.png"), 1);
const int cn = get<0>(GetParam());
const int kIndex = get<1>(GetParam());
const int dtype = get<2>(GetParam());
Size ksize = kernelSizeVec[kIndex];
Mat img, dstRef, dst;
convert(img_, img, dtype);
vector<Mat> channels;
split(img, channels);
channels.push_back(channels[0]); // channels size is 4.
Mat imgCn;
if (cn == 1)
imgCn = channels[0];
else if (cn == 4)
merge(channels, imgCn);
else
imgCn = img;
stackBlurRef(imgCn, dstRef, ksize);
stackBlur(imgCn, dst, ksize);
EXPECT_LE(cvtest::norm(dstRef, dst, NORM_INF), 2.);
}
INSTANTIATE_TEST_CASE_P(Imgproc, StackBlur,
testing::Combine(
testing::Values(1, 3, 4),
testing::Values(0, 1, 2, 3),
testing::Values(CV_8U, CV_16S, CV_16U, CV_32F)
)
);
typedef testing::TestWithParam<tuple<int> > StackBlur_GaussianBlur;
// StackBlur should produce similar results as GaussianBlur output.
TEST_P(StackBlur_GaussianBlur, compare)
{
Mat img_ = imread(findDataFile("shared/fruits.png"), 1);
const int dtype = get<0>(GetParam());
Size ksize(3, 3);
Mat img, dstS, dstG;
convert(img_, img, dtype);
stackBlur(img, dstS, ksize);
GaussianBlur(img, dstG, ksize, 0);
EXPECT_LE(cvtest::norm(dstS, dstG, NORM_INF), 13.);
}
INSTANTIATE_TEST_CASE_P(Imgproc, StackBlur_GaussianBlur, testing::Values(CV_8U, CV_16S, CV_16U, CV_32F));
}
}
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