Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving

By David Menotti, Laurent Najman, Jacques Facon, Arnaldo de Albuquerque Araújo. IEEE transactions on consumer electronics, 2007

300 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/6d39b8a8e0e24a4d6f74ba877db80d386122adad

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In Computer Vision and Pattern Recognition

1. Min-Gyo Chung
2. Mary Kim

Citations in the corpus

• Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement (2008, methodology): “As test images, we selected 10 images: couple, F16, jet, bottle, house, woman, U2, girl, Einstein, and copter, which have been previously used in many other methods to show their performances [1], [3], [4], [7].”