Available filters with parameters#

Overview of all implemented filters and their parameters with descriptions is listed below.

  • median blur

    • ksize (int) - Kernel size, determines how large of an area the filter processes.

  • gaussian blur

    • sigma (int) - Gaussian kernel standart deviation, determines the weight of further pixels on the currently processed pixel.

  • bilateral blur

    • diameter (int) - Diameter of pixel neighborhood used for filtering.

    • sigmaColor (int) - Determines the weight of pixels of different color.

    • sigmaSpace (int) - Determines the weight of further pixels.

  • bilateral_scikit

    • sigmaColor (float) - Determines the weight of pixels of different color.

    • sigmaSpace (float) - Determines the weight of further pixels.

  • nlmeans (non-local means)

    • patch_size (int) - Size of patches used for denoising.

    • patch_distance (int) - Distance in pixels where to search for patches.

    • h (float) - Cut-off distance, higher means more smoothed image.

  • total_variation

    • weight (float) - Denoising weight, determines how much the image will be denoised.

  • block_match

    • sigma (float)- Standart deviation

  • unsharp_mask_scikit

    • radius (int) - Radius of the gaussian filter.

    • amount (float) - Strength of the unsharp mask, determines how much of the mask will be used for filtering.

  • farid

  • meijering

  • sato

  • hessian

    • sigmas (float) - Standart deviations

  • invert

  • scale_values

  • binarize

    • threshold (int) - Value to cut differentiate pixels.

  • binarize_otsu

  • add_margin

    • margin (int) - Number of pixels to add to the sides of the image.

    • color (int) - Color value of newly added pixels.

  • erode

    • kernel (numpy matrix) - Shape of the kernel used to erode image.

  • dilate

    • kernel (numpy matrix)- Shape of the kernel used to dilate image.