Method Bm3dDenoising

Namespace

OpenCvSharp

Assembly

OpenCvSharp.dll

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.