Fixed readme

README.md

@@ -134,32 +134,40 @@ All the filters used and their parameters are described below.
 ## Available filters with parameters
 
 - median blur
+
     - ksize - Kernel size (int)
 
 - gaussian blur
+
     - sigma - Gaussian kernel standart deviation (int)
 
 - bilateral 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
+
     - sigmaColor - Standard deviation for grayvalue/color distance (float)
     - sigmaSpace - Standard deviation for range distance in pixels (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)
     
@@ -170,6 +178,7 @@ All the filters used and their parameters are described below.
 - sato
 
 - hessian
+
     - sigmas - ? (float)
 
 - invert
@@ -177,6 +186,7 @@ All the filters used and their parameters are described below.
 - scale_values
 
 - binarize
+
     - threshold - value to cut differentiate pixels (int)
     - maxval - maximal value (int) ??
     - type - ? (str)
@@ -184,13 +194,16 @@ All the filters used and their parameters are described below.
 - binarize_otsu
 
 - add_margin
+
     - margin - number of pixels to add to the sides of the image (int)
     - color - color value of newly added pixels (int)
 
 - erode
+
     - kernel - kernel shape (numpy.matrix)
 
 - dilate
+
     - kernel - kernel shape (numpy.matrix)
 
 # Comparison