diff --git a/docs/filters.md b/docs/filters.md
index 8866e34b..c00683a9 100644
--- a/docs/filters.md
+++ b/docs/filters.md
@@ -11,7 +11,8 @@ Filters are configured via the ROS parameter namespace `point_filters`.
 {
   point_filters:
     filter_type_a:
-      # config for filter_type_a goes here
+      parameter_1: 5
+      parameter_2: "abc"
     filter_type_b:
       # ...
 }
@@ -30,9 +31,13 @@ ros2 param set /hesai_ros_wrapper_node point_filters.filter_type_a ...'
 
 The following filter types are supported:
 
-| Filter Name            | Filter Type       |
-| ---------------------- | ----------------- |
-| Downsample Mask Filter | `downsample_mask` |
+| Filter Name            | Filter Type       | Hesai | Robosense | Velodyne |
+| ---------------------- | ----------------- | :---: | :-------: | :------: |
+| Downsample Mask Filter | `downsample_mask` |  ✅   |    ❌     |    ❌    |
+
+Compatibility:  
+✅: compatible  
+❌: incompatible
 
 Below, each filter type is documented in detail.
 
@@ -56,9 +61,9 @@ The input image is dithered to a boolean mask:
 
 The decoded points are then kept/discarded based on that mask:
 
-| ![Pointcloud density](filters/at128_test_roi_cloud.png)                                | ![Pointcloud closeup](filters/at128_test_roi_cloud_closeup.png) |
-| -------------------------------------------------------------------------------------- | --------------------------------------------------------------- |
-| Pointcloud output (2D azimuth-elevation view, points are blurred to visualize density) | Close-up view of (bottom left of the pointcloud)                |
+| ![Pointcloud density](filters/at128_test_roi_cloud.png)                                                                                               | ![Pointcloud closeup](filters/at128_test_roi_cloud_closeup.png)                                       |
+| ----------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- |
+| Pointcloud output. The original pointcloud had uniform density (all white). 2D azimuth-elevation view, points are blurred to better visualize density | Close-up view of a region with multiple different downsampling levels (bottom left of the pointcloud) |
 
 #### Configuration Options
 
@@ -89,13 +94,3 @@ ros2 param set /hesai_ros_wrapper_node point_filters.downsample_mask.path ""'
   - Currently, non-rotational LiDARs are not yet supported
 - Image editors like GIMP use perceptual color profiles, which can lead to unexpected results (more/less downsampling than expected). Check the generated `_dithered.png` mask to see if you are affected.
 - Dithering performed by Nebula is spatial only, meaning that it stays constant over time. Decoded points are checked against the nearest pixel in the dithered mask
-
-## Compatibility Chart
-
-| Filter          | Hesai | Robosense | Velodyne |
-| --------------- | :---: | :-------: | :------: |
-| Downsample Mask |  ✅   |    ❌     |    ❌    |
-
-Compatibility:  
-✅: compatible  
-❌: incompatible