Fixed readme

master
Rostislav Lán 2 years ago
parent a0ffab3593
commit e832dbd3f1

@ -133,65 +133,78 @@ All the filters used and their parameters are described below.
## Available filters with parameters ## Available filters with parameters
-median blur - median blur
-ksize - Kernel size (int)
-gaussian blur - ksize - Kernel size (int)
-sigma - Gaussian kernel standart deviation (int)
-bilateral blur - gaussian blur
-diameter - Diameter of pixel neighborhood used for filtering (int)
-sigmaColor - Standard deviation for grayvalue/color distance (int)
-sigmaSpace - Standard deviation for range distance in pixels (int)
-bilateral_scikit - sigma - Gaussian kernel standart deviation (int)
-sigmaColor - Standard deviation for grayvalue/color distance (float)
-sigmaSpace - Standard deviation for range distance in pixels (float)
-nlmeans (non-local means) - bilateral blur
-patch_size - Size of patches used for denoising (int)
-patch_distance - Distance in pixels where to search for patches (int)
-h - Cut-off distance, higher means more smoothed image (float)
-total_variation - diameter - Diameter of pixel neighborhood used for filtering (int)
-weight - Denoising weight. (float) - sigmaColor - Standard deviation for grayvalue/color distance (int)
- sigmaSpace - Standard deviation for range distance in pixels (int)
-block_match - bilateral_scikit
-sigma - ? (?)
-unsharp mask scikit - sigmaColor - Standard deviation for grayvalue/color distance (float)
-radius - Radius of the gaussian filter (int) - sigmaSpace - Standard deviation for range distance in pixels (float)
-amount - Strength of the unsharp mask (float)
- nlmeans (non-local means)
- patch_size - Size of patches used for denoising (int)
- patch_distance - Distance in pixels where to search for patches (int)
- h - Cut-off distance, higher means more smoothed image (float)
- total_variation
- weight - Denoising weight. (float)
- block_match
- sigma - ? (?)
- unsharp mask scikit
- radius - Radius of the gaussian filter (int)
- amount - Strength of the unsharp mask (float)
-farid - farid
- meijering
- sato
- hessian
- sigmas - ? (float)
- invert
-meijering - scale_values
-sato - binarize
-hessian - threshold - value to cut differentiate pixels (int)
-sigmas - ? (float) - maxval - maximal value (int) ??
- type - ? (str)
-invert - binarize_otsu
-scale_values - add_margin
-binarize - margin - number of pixels to add to the sides of the image (int)
-threshold - value to cut differentiate pixels (int) - color - color value of newly added pixels (int)
-maxval - maximal value (int) ??
-type - ? (str)
-binarize_otsu - erode
-add_margin - kernel - kernel shape (numpy.matrix)
-margin - number of pixels to add to the sides of the image (int)
-color - color value of newly added pixels (int)
-erode - dilate
-kernel - kernel shape (numpy.matrix)
-dilate - kernel - kernel shape (numpy.matrix)
-kernel - kernel shape (numpy.matrix)
# Comparison # Comparison

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