A Comparative Study of Histogram Equalization Based Image Enhancement Techniques for Brightness Preservation and Contrast Enhancement
Not on the map. Why?
Abstract (arXiv)
Histogram Equalization is a contrast enhancement technique in the image processing which uses the histogram of image. However histogram equalization is not the best method for contrast enhancement because the mean brightness of the output image is significantly different from the input image. There are several extensions of histogram equalization has been proposed to overcome the brightness preservation challenge. Contrast enhancement using brightness preserving bi-histogram equalization (BBHE) and Dualistic sub image histogram equalization (DSIHE) which divides the image histogram into two parts based on the input mean and median respectively then equalizes each sub histogram independently. This paper provides review of different popular histogram equalization techniques and experimental study based on the absolute mean brightness error (AMBE), peak signal to noise ratio (PSNR), Structure similarity index (SSI) and Entropy.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Nov 2013.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2024New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecturecited by 4
- 2021Edge Detection for Satellite Images without Deep Networkscited by 1
- 2025Deep Perceptual Enhancement for Medical Image Analysiscited by 1
- 2023Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Reviewcited by 0
- 2023SugarViT -- Multi-objective Regression of UAV Images with Vision Transformers and Deep Label Distribution Learning Demonstrated on Disease Severity Prediction in Sugar Beetcited by 0
- 2026Mam-App: A Novel Parameter-Efficient Mamba Model for Apple Leaf Disease Classificationcited by 0
- 2026Mam-App: A Novel Parameter-Efficient Mamba Model for Apple Leaf Disease Classification29 Jan 2026
- 2025Deep Perceptual Enhancement for Medical Image Analysis11 Mar 2025
- 2024New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecture23 Oct 2024
- 2023SugarViT -- Multi-objective Regression of UAV Images with Vision Transformers and Deep Label Distribution Learning Demonstrated on Disease Severity Prediction in Sugar Beet6 Nov 2023
- 2023Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review14 Aug 2023
- 2021Edge Detection for Satellite Images without Deep Networks26 May 2021