Here are the key advantages and disadvantages of adaptive histogram equalization:
Advantages:
- It improves contrast in images and enhances features that are difficult to see. This makes low-contrast objects more visible.
- It adapts to local changes in an image. This prevents over-amplification of noise that can occur with regular histogram equalization.
Disadvantages:
- It may amplify noise in relatively flat or uniform areas of an image.
- Artificial boundaries may appear at boundaries between tiles used for local adaptation. This can be reduced by using larger tile sizes.
- It is a more computationally intensive process than regular histogram equalization since it requires calculating histograms for multiple tiles.
In summary,