Adaptive Histogram Equalization
Adaptive Histogram Equalization
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As an alternative to using Histogram Equalization (HE), we can perform contrast-limited adaptive histogram equalization (CLAHE). While Histogram Equalization works on the entire image, Adaptive Histogram Equalization operates on small regions in the image, called tiles. Adaptive Histogram Equalization enhances the contrast of each tile, so that the histogram of the output region approximately matches a specified histogram. After performing the equalization, CLAHE combines neighboring tiles using bilinear interpolation to eliminate artificially induced boundaries.
We found this Adaptive Histogram Equalization works the best among all the methods that we have implemented for contrasting.
Advantages:
It computes the HE of the distinct sections of the image
It preserves the edges in distinct regions of the image
it enhances the contrast locally.
Disadvantage:
AHE overamplifies the noise in relatively homogenous regions of an image.
To prevent this a variant of adaptive histogram equalization called contrast limited adaptive histogram equalization (CLAHE) is used.
Sample I: Fruits
Sample I: Fruits
Image of Fruits Before CLAHE
Image of Fruits After CLAHE
Sample II: Valley
Sample II: Valley
Image of Valley Before CLAHE
Image of Valley After CLAHE
Sample III: Reindeer
Sample III: Reindeer
Image of Reindeer Before CLAHE
Image of Reindeer After CLAHE
Sample IV: Person
Sample IV: Person
Image of Person Before CLAHE
Image of Person After CLAHE
Sample V: Scenery
Sample V: Scenery
Image of Scenery Before CLAHE
Image of Scenery After CLAHE
Sample VI: Text
Sample VI: Text
Image of Text Before CLAHE
Image of Text After CLAHE
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