Class CvXPhoto

cv::xphoto functions

Inheritance

System.Object

CvXPhoto

Inherited Members

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace: OpenCvSharp.XPhoto

Assembly: OpenCvSharp.dll

Syntax

public static class CvXPhoto

Methods

ApplyChannelGains(InputArray, OutputArray, Single, Single, Single)

Implements an efficient fixed-point approximation for applying channel gains, which is the last step of multiple white balance algorithms.

Declaration

public static void ApplyChannelGains(InputArray src, OutputArray dst, float gainB, float gainG, float gainR)

Parameters

Type	Name	Description
InputArray	src	Input three-channel image in the BGR color space (either CV_8UC3 or CV_16UC3)
OutputArray	dst	Output image of the same size and type as src.
System.Single	gainB	gain for the B channel
System.Single	gainG	gain for the G channel
System.Single	gainR	gain for the R channel

Bm3dDenoising(InputArray, InputOutputArray, OutputArray, Single, Int32, Int32, Int32, Int32, Int32, Int32, Single, NormTypes, Bm3dSteps, TransformTypes)

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.

Declaration

public static void Bm3dDenoising(InputArray src, InputOutputArray dstStep1, OutputArray dstStep2, float h = 1F, int templateWindowSize = 4, int searchWindowSize = 16, int blockMatchingStep1 = 2500, int blockMatchingStep2 = 400, int groupSize = 8, int slidingStep = 1, float beta = 2F, NormTypes normType = NormTypes.L2, Bm3dSteps step = Bm3dSteps.STEPALL, TransformTypes transformType = TransformTypes.HAAR)

Parameters

Type	Name	Description
InputArray	src	Input 8-bit or 16-bit 1-channel image.
InputOutputArray	dstStep1	Output image of the first step of BM3D with the same size and type as src.
OutputArray	dstStep2	Output image of the second step of BM3D with the same size and type as src.
System.Single	h	Parameter regulating filter strength. Big h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise.
System.Int32	templateWindowSize	Size in pixels of the template patch that is used for block-matching. Should be power of 2.
System.Int32	searchWindowSize	Size in pixels of the window that is used to perform block-matching. Affect performance linearly: greater searchWindowsSize - greater denoising time. Must be larger than templateWindowSize.
System.Int32	blockMatchingStep1	Block matching threshold for the first step of BM3D (hard thresholding), i.e.maximum distance for which two blocks are considered similar.Value expressed in euclidean distance.
System.Int32	blockMatchingStep2	Block matching threshold for the second step of BM3D (Wiener filtering), i.e.maximum distance for which two blocks are considered similar. Value expressed in euclidean distance.
System.Int32	groupSize	Maximum size of the 3D group for collaborative filtering.
System.Int32	slidingStep	Sliding step to process every next reference block.
System.Single	beta	Kaiser window parameter that affects the sidelobe attenuation of the transform of the window.Kaiser window is used in order to reduce border effects.To prevent usage of the window, set beta to zero.
NormTypes	normType	Norm used to calculate distance between blocks. L2 is slower than L1 but yields more accurate results.
Bm3dSteps	step	Step of BM3D to be executed. Allowed are only BM3D_STEP1 and BM3D_STEPALL. BM3D_STEP2 is not allowed as it requires basic estimate to be present.
TransformTypes	transformType	Type of the orthogonal transform used in collaborative filtering step. Currently only Haar transform is supported.

Bm3dDenoising(InputArray, OutputArray, Single, Int32, Int32, Int32, Int32, Int32, Int32, Single, NormTypes, Bm3dSteps, TransformTypes)

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.

Declaration

public static void Bm3dDenoising(InputArray src, OutputArray dst, float h = 1F, int templateWindowSize = 4, int searchWindowSize = 16, int blockMatchingStep1 = 2500, int blockMatchingStep2 = 400, int groupSize = 8, int slidingStep = 1, float beta = 2F, NormTypes normType = NormTypes.L2, Bm3dSteps step = Bm3dSteps.STEPALL, TransformTypes transformType = TransformTypes.HAAR)

Parameters

Type	Name	Description
InputArray	src	Input 8-bit or 16-bit 1-channel image.
OutputArray	dst	Output image with the same size and type as src.
System.Single	h	Parameter regulating filter strength. Big h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise.
System.Int32	templateWindowSize	Size in pixels of the template patch that is used for block-matching. Should be power of 2.
System.Int32	searchWindowSize	Size in pixels of the window that is used to perform block-matching. Affect performance linearly: greater searchWindowsSize - greater denoising time. Must be larger than templateWindowSize.
System.Int32	blockMatchingStep1	Block matching threshold for the first step of BM3D (hard thresholding), i.e.maximum distance for which two blocks are considered similar.Value expressed in euclidean distance.
System.Int32	blockMatchingStep2	Block matching threshold for the second step of BM3D (Wiener filtering), i.e.maximum distance for which two blocks are considered similar. Value expressed in euclidean distance.
System.Int32	groupSize	Maximum size of the 3D group for collaborative filtering.
System.Int32	slidingStep	Sliding step to process every next reference block.
System.Single	beta	Kaiser window parameter that affects the sidelobe attenuation of the transform of the window.Kaiser window is used in order to reduce border effects.To prevent usage of the window, set beta to zero.
NormTypes	normType	Norm used to calculate distance between blocks. L2 is slower than L1 but yields more accurate results.
Bm3dSteps	step	Step of BM3D to be executed. Allowed are only BM3D_STEP1 and BM3D_STEPALL. BM3D_STEP2 is not allowed as it requires basic estimate to be present.
TransformTypes	transformType	Type of the orthogonal transform used in collaborative filtering step. Currently only Haar transform is supported.

CreateGrayworldWB()

Creates an instance of GrayworldWB

Declaration

public static GrayworldWB CreateGrayworldWB()

Returns

Type	Description
GrayworldWB

CreateLearningBasedWB(String)

Creates an instance of LearningBasedWB

Declaration

public static LearningBasedWB CreateLearningBasedWB(string model)

Parameters

Type	Name	Description
System.String	model	Path to a .yml file with the model. If not specified, the default model is used

Returns

Type	Description
LearningBasedWB

CreateSimpleWB()

Creates an instance of SimpleWB

Declaration

public static SimpleWB CreateSimpleWB()

Returns

Type	Description
SimpleWB

DctDenoising(Mat, Mat, Double, Int32)

The function implements simple dct-based denoising

Declaration

public static void DctDenoising(Mat src, Mat dst, double sigma, int psize = 16)

Parameters

Type	Name	Description
Mat	src	source image
Mat	dst	destination image
System.Double	sigma	expected noise standard deviation
System.Int32	psize	size of block side where dct is computed

Remarks

http://www.ipol.im/pub/art/2011/ys-dct/

Inpaint(Mat, Mat, Mat, InpaintTypes)

The function implements different single-image inpainting algorithms.

Declaration

public static void Inpaint(Mat src, Mat mask, Mat dst, InpaintTypes algorithm)

Parameters

Type	Name	Description
Mat	src	source image, it could be of any type and any number of channels from 1 to 4. In case of 3- and 4-channels images the function expect them in CIELab colorspace or similar one, where first color component shows intensity, while second and third shows colors. Nonetheless you can try any colorspaces.
Mat	mask	mask (CV_8UC1), where non-zero pixels indicate valid image area, while zero pixels indicate area to be inpainted
Mat	dst	destination image
InpaintTypes	algorithm	see OpenCvSharp.XPhoto.InpaintTypes

OilPainting(InputArray, OutputArray, Int32, Int32, Nullable<ColorConversionCodes>)

oilPainting. See the book @cite Holzmann1988 for details.

Declaration

public static void OilPainting(InputArray src, OutputArray dst, int size, int dynRatio, ColorConversionCodes? code = null)

Parameters

Type	Name	Description
InputArray	src	Input three-channel or one channel image (either CV_8UC3 or CV_8UC1)
OutputArray	dst	Output image of the same size and type as src.
System.Int32	size	neighbouring size is 2-size+1
System.Int32	dynRatio	image is divided by dynRatio before histogram processing
System.Nullable<ColorConversionCodes>	code	color space conversion code(see ColorConversionCodes). Histogram will used only first plane