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

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Conflicts:
	cmake/OpenCVDetectAndroidSDK.cmake
	cmake/OpenCVGenAndroidMK.cmake
	cmake/OpenCVModule.cmake
	cmake/templates/OpenCV.mk.in
	cmake/templates/OpenCVConfig.cmake.in
	doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst
	modules/cudabgsegm/src/cuda/mog.cu
	modules/imgproc/perf/opencl/perf_filters.cpp
	modules/imgproc/src/opencl/filterSep_singlePass.cl
	modules/nonfree/CMakeLists.txt
	modules/nonfree/perf/perf_precomp.hpp
	modules/ocl/perf/perf_haar.cpp
	modules/ocl/src/filtering.cpp
	modules/ocl/src/opencl/bgfg_mog.cl
	modules/superres/CMakeLists.txt
	modules/superres/src/btv_l1_cuda.cpp
	modules/superres/src/cuda/btv_l1_gpu.cu
	modules/superres/src/frame_source.cpp
	modules/superres/src/input_array_utility.cpp
	modules/superres/src/optical_flow.cpp
	modules/superres/src/precomp.hpp
	samples/gpu/CMakeLists.txt
	samples/gpu/brox_optical_flow.cpp
	samples/gpu/super_resolution.cpp
This commit is contained in:
Roman Donchenko
2014-03-24 15:47:56 +04:00
parent 623b1db8d1 bcb0ee3e4b
commit cc05493730
57 changed files with 364 additions and 236 deletions
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6
doc/tutorials/core/adding_images/adding_images.rst
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@@ -6,12 +6,12 @@ Adding (blending) two images using OpenCV
Goal
=====
In this tutorial you will learn how to:
In this tutorial you will learn:
.. container:: enumeratevisibleitemswithsquare
* What is *linear blending* and why it is useful.
* Add two images using :add_weighted:`addWeighted <>`
* what is *linear blending* and why it is useful;
* how to add two images using :add_weighted:`addWeighted <>`
Theory
=======

2
doc/tutorials/core/how_to_scan_images/how_to_scan_images.rst
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@@ -18,7 +18,7 @@ We'll seek answers for the following questions:
Our test case
=============
Let us consider a simple color reduction method. Using the unsigned char C and C++ type for matrix item storing a channel of pixel may have up to 256 different values. For a three channel image this can allow the formation of way too many colors (16 million to be exact). Working with so many color shades may give a heavy blow to our algorithm performance. However, sometimes it is enough to work with a lot less of them to get the same final result.
Let us consider a simple color reduction method. By using the unsigned char C and C++ type for matrix item storing, a channel of pixel may have up to 256 different values. For a three channel image this can allow the formation of way too many colors (16 million to be exact). Working with so many color shades may give a heavy blow to our algorithm performance. However, sometimes it is enough to work with a lot less of them to get the same final result.
In this cases it's common that we make a *color space reduction*. This means that we divide the color space current value with a new input value to end up with fewer colors. For instance every value between zero and nine takes the new value zero, every value between ten and nineteen the value ten and so on.