title: Adaptive threshold Binarization's bad effects
body: <p>I implemented some adaptive binarization methods, they use a small window and at each pixel the threshold value is calculated. There are problems with these methods:
  If we select the window size too small we will get this effect (I think the reason is because of window size is small)
  <a href="https://i.stack.imgur.com/jx8wB.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/jx8wB.jpg" alt="alt text"></a><br>
  <sub>(source: <a href="http://i.piccy.info/i4/3d/bc/773b7df74ff7dadfd11c09372b7e.jpeg" rel="nofollow noreferrer">piccy.info</a>)</sub>  </p>
  
  <p>At the left upper corner there is an original image, right upper corner - global threshold result. Bottom left - example of dividing image to some parts (but I am talking about analyzing image's pixel small surrounding, for example window of size 10X10).
  So you can see the result of such algorithms at the bottom right picture, we got a black area, but it must be white.
  Does anybody know how to improve an algorithm to solve this problem?</p>