Add adaptive histogram equalization algorithm #516
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
Adaptive histogram equalization(AHE) is used in cases when histogram equalization cannot properly contrast enhance due to the presence of both very bright and very dark regions.
AHE brings out the local information in an image by dividing the image into tiles and then individually performs HE on each of them. Later to remove tiling artefacts a bi-linear interpolation is performed using mappings from the adjacent tiles. Finally to suppress noise, use contrast clipping to limit the #pixels of a particular value.
This PR adds code, tests & an example to show how to use the GIL AHE algorithm.
Dependency
This PR requires support of GIL histogram class and the global HE algorithm currently running in PR #499 & PR #514 respectively . Reviewing and merging can only be done post completion of former PRs.
References
Tasklist