Performs image denoising using the Block-Matching and 3D-filtering algorithm

dst = cv.bm3dDenoising(src)
[dstStep1, dstStep2] = cv.bm3dDenoising(src)
[...] = cv.bm3dDenoising(..., 'OptionName',optionValue, ...)

Input

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

Output

• dst Output image with the same size and type as src.
• dstStep1 Output image of the first step of BM3D with the same size and type as src. Basic image must be provided.
• dstStep2 Output image of the second step of BM3D with the same size and type as src.

Options

• Basic Basic image, initial estimate of the first step. Must be provided in the case of Step=2.
• 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. default 1
• TemplateWindowSize Size in pixels of the template patch that is used for block-matching. Should be power of 2. default 4
• 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. default 16
• 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. default 2500
• 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. default 400
• GroupSize Maximum size of the 3D group for collaborative filtering. default 8
• SlidingStep Sliding step to process every next reference block. default 1
• 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. default 2.0
• NormType Norm used to calculate distance between blocks. L2 is slower than L1 but yields more accurate results. default 'L2'. One:
  • L2
  • L1
• Step Step of BM3D to be executed. Possible variants are: step 1, step 2, both steps. In the first variant, allowed are only '1' and 'All'. '2' is not allowed as it requires Basic estimate to be present. One of:
  • All (default) Execute all steps of the algorithm.
  • 1 Execute only first step of the algorithm.
  • 2 Execute only second step of the algorithm.
• TransformType Type of the orthogonal transform used in collaborative filtering step. Currently only Haar transform is supported. One of:
  • Haar (default) Un-normalized Haar transform.

Performs image denoising using the Block-Matching and 3D-filtering algorithm PDF with several computational optimizations. Noise expected to be a gaussian white noise.

This function expected to be applied to grayscale images. Advanced usage of this function can be manual denoising of colored image in different colorspaces.

Note: This algorithm is patented and is excluded in the default configuration; Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library.