Table of Contents

Class CvXPhoto

Namespace
OpenCvSharp.XPhoto
Assembly
OpenCvSharp.dll

cv::xphoto functions

public static class CvXPhoto
Inheritance
CvXPhoto
Inherited Members

Methods

ApplyChannelGains(InputArray, OutputArray, float, float, float)

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

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

Parameters

src InputArray

Input three-channel image in the BGR color space (either CV_8UC3 or CV_16UC3)

dst OutputArray

Output image of the same size and type as src.

gainB float

gain for the B channel

gainG float

gain for the G channel

gainR float

gain for the R channel

Bm3dDenoising(InputArray, InputOutputArray, OutputArray, float, int, int, int, int, int, int, float, 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.

public static 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, NormTypes normType = NormTypes.L2, Bm3dSteps step = Bm3dSteps.STEPALL, TransformTypes transformType = TransformTypes.HAAR)

Parameters

src InputArray

Input 8-bit or 16-bit 1-channel image.

dstStep1 InputOutputArray

Output image of the first step of BM3D with the same size and type as src.

dstStep2 OutputArray

Output image of the second step of BM3D with the same size and type as src.

h float

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.

templateWindowSize int

Size in pixels of the template patch that is used for block-matching. Should be power of 2.

searchWindowSize int

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.

blockMatchingStep1 int

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.

blockMatchingStep2 int

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.

groupSize int

Maximum size of the 3D group for collaborative filtering.

slidingStep int

Sliding step to process every next reference block.

beta float

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.

normType NormTypes

Norm used to calculate distance between blocks. L2 is slower than L1 but yields more accurate results.

step Bm3dSteps

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.

transformType TransformTypes

Type of the orthogonal transform used in collaborative filtering step. Currently only Haar transform is supported.

Bm3dDenoising(InputArray, OutputArray, float, int, int, int, int, int, int, float, 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.

public static 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, NormTypes normType = NormTypes.L2, Bm3dSteps step = Bm3dSteps.STEPALL, TransformTypes transformType = TransformTypes.HAAR)

Parameters

src InputArray

Input 8-bit or 16-bit 1-channel image.

dst OutputArray

Output image with the same size and type as src.

h float

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.

templateWindowSize int

Size in pixels of the template patch that is used for block-matching. Should be power of 2.

searchWindowSize int

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.

blockMatchingStep1 int

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.

blockMatchingStep2 int

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.

groupSize int

Maximum size of the 3D group for collaborative filtering.

slidingStep int

Sliding step to process every next reference block.

beta float

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.

normType NormTypes

Norm used to calculate distance between blocks. L2 is slower than L1 but yields more accurate results.

step Bm3dSteps

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.

transformType TransformTypes

Type of the orthogonal transform used in collaborative filtering step. Currently only Haar transform is supported.

CreateGrayworldWB()

Creates an instance of GrayworldWB

public static GrayworldWB CreateGrayworldWB()

Returns

GrayworldWB

CreateLearningBasedWB(string?)

Creates an instance of LearningBasedWB

public static LearningBasedWB CreateLearningBasedWB(string? model)

Parameters

model string

Path to a .yml file with the model. If not specified, the default model is used

Returns

LearningBasedWB

CreateSimpleWB()

Creates an instance of SimpleWB

public static SimpleWB CreateSimpleWB()

Returns

SimpleWB

DctDenoising(Mat, Mat, double, int)

The function implements simple dct-based denoising

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

Parameters

src Mat

source image

dst Mat

destination image

sigma double

expected noise standard deviation

psize int

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.

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

Parameters

src Mat

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.

mask Mat

mask (CV_8UC1), where non-zero pixels indicate valid image area, while zero pixels indicate area to be inpainted

dst Mat

destination image

algorithm InpaintTypes

see OpenCvSharp.XPhoto.InpaintTypes

OilPainting(InputArray, OutputArray, int, int, ColorConversionCodes?)

oilPainting. See the book @cite Holzmann1988 for details.

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

Parameters

src InputArray

Input three-channel or one channel image (either CV_8UC3 or CV_8UC1)

dst OutputArray

Output image of the same size and type as src.

size int

neighbouring size is 2-size+1

dynRatio int

image is divided by dynRatio before histogram processing

code ColorConversionCodes?

color space conversion code(see ColorConversionCodes). Histogram will used only first plane

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