estimate_laser_plane.md

@@ -33,13 +33,13 @@ The inverse transformation from ![alt text](http://mathurl.com/hw2kh9a.png) to !
 
 ### Tracking laser points in image
 
-In first, when we want to track a laser path, we convert an image with the laser path to the grayscale image with custom channel weights. The most significant influence is given to red channel, green one takes one quarter, and blue is almost ignored. The following picture is using R:G:B ratio 70:25:5.
+In first, when we want to track a laser path, the image with the laser path is converted to the grayscale image with the highest proportion to a Red channel.
 
 ![result_cal_up_gray](http://gitlab.ciirc.cvut.cz/cmirajak/laser_plane_scanner/uploads/6a5bd62aa4bb7f974336439accd5415e/result_cal_up_gray.png)
 
-As you can see on the picture above the laser path has slightly higher intensity than anything around. Therefore, we determine the laser position with pixel precision as the pixel with maximal intensity in some direction (i.e., row/column). 
+As you can see in the picture above, the laser path has slightly higher intensity than anything around. The laser position is given as a pixel with maximal intensity in some direction (i.e., row/column). 
 
-To refine it, we know that the laser light should have a normal distribution around the maximum. Hence, we choose the specific neighborhood around maximum and calculate the logarithm of intensities inside of it. These points are describing some parabola now. Due to that we use LSQ and fit one there. Finally, we call its local maximum as a place with maximal intensity in a specific direction. 
+A laser light has a normal distribution around the maximum. This assumption is used to refine laser position to sub-pixel precision. The neighborhood around maximum is chosen and intensities are logarithmized. These logarithms now describe a parabola. Finally, the parabola local maximum is a place with maximal intensity in our specified direction. 
 
 ### Estimating Laser Plane Position