Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization

By Qing Wang, Rabab Kreidieh Ward. IEEE transactions on consumer electronics, 2007

446 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/163facc12521ac17fcb275fb5982f4ae2dd59a55

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Min-Gyo Chung
2. Chulwoo Lee
3. Mary Kim
4. Chang-Su Kim
5. Yu Li
6. Xiaojie Guo
7. Feng Lu
8. Feifan Lv

Citations in the corpus

• Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement (2008, methodology): “The method proposed in [6] also employs the power law function for weighting, but it uses only a single power index and the two internal parameters including the power index should be manually tuned by end-users in order to obtain the output image with desirable contrast enhancement.”
• Contrast Enhancement Based on Layered Difference Representation of 2D Histograms (2013, background): “The layered difference representation (LDR): the transformation function x = [x0, x1, · · · , x255]T and the difference variables dlk’s are shown in a tree-like pyramidal structure.”