An advanced contrast enhancement using partially overlapped sub-block histogram equalization
By Joung-Youn Kim, L. Kim, Seung-Ho Hwang. 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000
659 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/862ff0e1fe1f6db9ef6435c71b3135595c906100
How researchers see this paper
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In Computer Vision and Pattern Recognition
- Xiangjun Shi
- Dinu Coltuc
- Mohammad Abdullah-Al-Wadud
- M. Ali Akber Dewan
- Ling Shao
- Heng-Da Cheng
- Oksam Chae
- Chulwoo Lee
Citations in the corpus
- An Experiment-Based Review of Low-Light Image Enhancement Methods (2020, methodology): “For example, a standard adaptive histogram equalization (AHE) algorithm was proposed in [78], while in [79], a block iterative histogram method was used to enhance the image contrast, and a moving template was used for partially overlapped subblock histogram equalization (POSHE) processing for each…”
- Optimized contrast enhancement for real-time image and video dehazing (2013, methodology): “Therefore, we sample the evaluation points using the partially overlapping sub-block scheme in [29] and employ centered windows, instead of shiftable windows, for video dehazing.”
- Contrast Enhancement Based on Layered Difference Representation of 2D Histograms (2013, background): “[2]–[6], derives and applies the transformation function for each pixel adaptively according to the information in a local neighborhood.”
- A simple and effective histogram equalization approach to image enhancement (2004, methodology): “Another method uses local histogram modification to enhance image contrast in a local area [1,2,6,11,16,19,21,26], such as: (1) local”
- A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior (2015, positive): “dehazing methods [15]–[17]).”
- Exact histogram specification (2006, background): “Contrast enhancement by local (adaptive) histogram specification has received much attention in the literature [14]–[16].”
- A Dynamic Histogram Equalization for Image Contrast Enhancement (2007, methodology): “Generally, we can classify these methods in two principle categories – global and local histogram equalization [14].”