cv::xphoto Namespace Reference

Classes
class	GrayworldWB
	Gray-world white balance algorithm. More...
class	LearningBasedWB
	More sophisticated learning-based automatic white balance algorithm. More...
class	SimpleWB
	A simple white balance algorithm that works by independently stretching each of the input image channels to the specified range. For increased robustness it ignores the top and bottom \(p\%\) of pixel values. More...
class	TonemapDurand
	This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter and compresses contrast of the base layer thus preserving all the details. More...
class	WhiteBalancer
	The base class for auto white balance algorithms. More...

Enumerations
enum	Bm3dSteps {   BM3D_STEPALL = 0,   BM3D_STEP1 = 1,   BM3D_STEP2 = 2 }
	BM3D algorithm steps. More...
enum	InpaintTypes { INPAINT_SHIFTMAP = 0 }
	various inpainting algorithms More...
enum	TransformTypes { HAAR = 0 }
	BM3D transform types. More...

Functions
void	applyChannelGains (InputArray src, OutputArray dst, float gainB, float gainG, float gainR)
	Implements an efficient fixed-point approximation for applying channel gains, which is the last step of multiple white balance algorithms.
void	bm3dDenoising (InputArray src, InputOutputArray dstStep1, OutputArray dstStep2, float h=1, int templateWindowSize=4, int searchWindowSize=16, int blockMatchingStep1=2500, int blockMatchingStep2=400, int groupSize=8, int slidingStep=1, float beta=2.0f, int normType=cv::NORM_L2, int step=cv::xphoto::BM3D_STEPALL, int transformType=cv::xphoto::HAAR)
	Performs image denoising using the Block-Matching and 3D-filtering algorithm http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf with several computational optimizations. Noise expected to be a gaussian white noise.
void	bm3dDenoising (InputArray src, OutputArray dst, float h=1, int templateWindowSize=4, int searchWindowSize=16, int blockMatchingStep1=2500, int blockMatchingStep2=400, int groupSize=8, int slidingStep=1, float beta=2.0f, int normType=cv::NORM_L2, int step=cv::xphoto::BM3D_STEPALL, int transformType=cv::xphoto::HAAR)
	Performs image denoising using the Block-Matching and 3D-filtering algorithm http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf with several computational optimizations. Noise expected to be a gaussian white noise.
Ptr< GrayworldWB >	createGrayworldWB ()
	Creates an instance of GrayworldWB.
Ptr< LearningBasedWB >	createLearningBasedWB (const String &path_to_model=String())
	Creates an instance of LearningBasedWB.
Ptr< SimpleWB >	createSimpleWB ()
	Creates an instance of SimpleWB.
Ptr< TonemapDurand >	createTonemapDurand (float gamma=1.0f, float contrast=4.0f, float saturation=1.0f, float sigma_space=2.0f, float sigma_color=2.0f)
	Creates TonemapDurand object.
void	dctDenoising (const Mat &src, Mat &dst, const double sigma, const int psize=16)
	The function implements simple dct-based denoising.
void	inpaint (const Mat &src, const Mat &mask, Mat &dst, const int algorithmType)
	The function implements different single-image inpainting algorithms.
void	oilPainting (InputArray src, OutputArray dst, int size, int dynRatio, int code)
	oilPainting See the book
void	oilPainting (InputArray src, OutputArray dst, int size, int dynRatio)
	oilPainting See the book