Added missing parameters to readme.

README.md

@@ -12,8 +12,10 @@ This model can either be planar, curved or mapped.
 
 # Prerequisites
 
-For now this is only viable for ubuntu gnu/linux machines.
+For now this has only been tested on Ubuntu gnu/linux machines.
-It should however be possible to run it in WSL and virtual machines of most linux distributions.
+It should however be possible to run it in on most distributions, WSL and virtual machines of most linux distributions.
+
+This guide is for Ubuntu machines only.
 Before cloning repository, you need these to succesfully use the application.
 
 * python version 3.10 is a requirement might work on earlier python 3 versions
@@ -148,47 +150,47 @@ There is also an option to save current command line setting as a preset using -
     python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_cline.png 600 -d preset_gaussian gaussian sigma=1
     ```
 
-List of all implemented filters and their parameters is described below.
-
 ## Available filters with parameters
 
+Overview of all implemented filters and their parameters with descriptions is listed below.
+
 - median blur
 
-    - ksize - Kernel size (int)
+    - ksize (int) - Kernel size, determines how large of an area the filter processes.
 
 - gaussian blur
 
-    - sigma - Gaussian kernel standart deviation (int)
+    - sigma (int) - Gaussian kernel standart deviation, determines the weight of further pixels on the currently processed pixel.
 
 - bilateral blur
 
-    - diameter - Diameter of pixel neighborhood used for filtering (int)
+    - diameter (int) - Diameter of pixel neighborhood used for filtering.
-    - sigmaColor - Standard deviation for grayvalue/color distance (int)
+    - sigmaColor (int) - Determines the weight of pixels of different color.
-    - sigmaSpace - Standard deviation for range distance in pixels (int)
+    - sigmaSpace (int) - Determines the weight of further pixels.
 
 - bilateral_scikit
 
-    - sigmaColor - Standard deviation for grayvalue/color distance (float)
+    - sigmaColor (float) - Determines the weight of pixels of different color.
-    - sigmaSpace - Standard deviation for range distance in pixels (float)
+    - sigmaSpace (float) - Determines the weight of further pixels.
 
 - nlmeans (non-local means) 
 
-    - patch_size - Size of patches used for denoising (int)
+    - patch_size (int) - Size of patches used for denoising.
-    - patch_distance - Distance in pixels where to search for patches (int)
+    - patch_distance (int) - Distance in pixels where to search for patches.
-    - h - Cut-off distance, higher means more smoothed image (float)
+    - h (float) - Cut-off distance, higher means more smoothed image.
 
 - total_variation
 
-    - weight - Denoising weight. (float)
+    - weight (float) - Denoising weight, determines how much the image will be denoised.
 
 - block_match
 
-    - sigma - ? (?)
+    - sigma (float)- Standart deviation
 
 - unsharp mask scikit
 
-    - radius - Radius of the gaussian filter (int)
+    - radius (int) - Radius of the gaussian filter.
-    - amount - Strength of the unsharp mask (float)
+    - amount (float) - Strength of the unsharp mask, determines how much of the mask will be used for filtering.
     
 - farid
 
@@ -198,7 +200,7 @@ List of all implemented filters and their parameters is described below.
 
 - hessian
 
-    - sigmas - ? (float)
+    - sigmas (float) - Standart deviations
 
 - invert
 
@@ -206,24 +208,22 @@ List of all implemented filters and their parameters is described below.
 
 - binarize
 
-    - threshold - value to cut differentiate pixels (int)
+    - threshold (int) - Value to cut differentiate pixels.
-    - maxval - maximal value (int) ??
-    - type - ? (str)
 
 - binarize_otsu
 
 - add_margin
 
-    - margin - number of pixels to add to the sides of the image (int)
+    - margin (int) - Number of pixels to add to the sides of the image.
-    - color - color value of newly added pixels (int)
+    - color (int) - Color value of newly added pixels.
 
 - erode
 
-    - kernel - kernel shape (numpy.matrix)
+    - kernel (numpy matrix) - Shape of the kernel used to erode image.
 
 - dilate
 
-    - kernel - kernel shape (numpy.matrix)
+    - kernel (numpy matrix)- Shape of the kernel used to dilate image.
 
 # Comparison