Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution

This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed ima...

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Bibliographic Details
Published in:IEEE transactions on image processing 2013-03, Vol.22 (3), p.1032-1041
Main Authors: HUANG, Shih-Chia, CHENG, Fan-Chieh, CHIU, Yi-Sheng
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial intelligence
Brightness
Computer science
control theory
systems
Contrast enhancement
Data Interpretation, Statistical
Detection, estimation, filtering, equalization, prediction
Digital
Digital images
Entropy
Equations
Exact sciences and technology
gamma correction
histogram equalization
histogram modification
Histograms
Image color analysis
Image contrast
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Information, signal and communications theory
Luminance
Mathematical model
Pattern recognition
Pattern recognition. Digital image processing. Computational geometry
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal, noise
State of the art
Statistical Distributions
Telecommunications and information theory
Transformations
Video Recording - methods
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Summary:This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels. To enhance video, the proposed image-enhancement method uses temporal information regarding the differences between each frame to reduce computational complexity. Experimental results demonstrate that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2012.2226047