Adaptive histogram equalization

Adaptive histogram equalization is like coloring in a picture. Imagine you have a picture of a house with a red roof and green grass. But the rest of the picture is kind of gray and it's hard to see the details. If you color the picture, you can make the details stand out.

In the same way, adaptive histogram equalization takes a picture and makes it easier to see the details. But instead of coloring, it changes the brightness and contrast of the picture.

The algorithm works like this:

1. The picture is divided into small sections called "tiles".
2. A histogram is created for each tile. A histogram shows how many pixels in the tile have a certain brightness.
3. The histogram is "equalized". This means that the brightness levels are spread out evenly. So if there were a lot of pixels with brightness level 50, they might all be changed to brightness level 75.
4. Finally, the tile is put back into the picture.

By doing this for every tile, the picture becomes brighter and the details become easier to see.

Adaptive histogram equalization is especially useful for pictures with a lot of contrast. For example, if you took a picture of a street at night, the bright streetlights might make it hard to see the dark shadows. Adaptive histogram equalization could make the shadows brighter without making the streetlights too bright.

In short, adaptive histogram equalization is like coloring in a picture to make the details stand out, but instead of coloring it changes the brightness and contrast.