Quadrant Dynamic with Automatic Plateau Limit Histogram Equalization for Image Enhancement

The fundamental and important preprocessing stage in image processing is the image contrast enhancement technique. Histogram equalization is an effective contrast enhancement technique. In this paper, a histogram equalization based technique called quadrant dynamic with automatic plateau limit histo...

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Bibliographic Details
Published in:Mathematical problems in engineering 2014-01, Vol.2014 (2014), p.1-8
Main Authors: Jagatheeswari, P., Mary Linda, M., Suresh Kumar, S.
Format: Article
Language:English
Subjects:
Algorithms
Automation
Brightness
Dynamics
Equalization
Histograms
Image contrast
Image enhancement
Image filters
Image processing
Mathematical analysis
Mathematical problems
Methods
Noise
Quadrants
Qualitative analysis
Standard deviation
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Summary:The fundamental and important preprocessing stage in image processing is the image contrast enhancement technique. Histogram equalization is an effective contrast enhancement technique. In this paper, a histogram equalization based technique called quadrant dynamic with automatic plateau limit histogram equalization (QDAPLHE) is introduced. In this method, a hybrid of dynamic and clipped histogram equalization methods are used to increase the brightness preservation and to reduce the overenhancement. Initially, the proposed QDAPLHE algorithm passes the input image through a median filter to remove the noises present in the image. Then the histogram of the filtered image is divided into four subhistograms while maintaining second separated point as the mean brightness. Then the clipping process is implemented by calculating automatically the plateau limit as the clipped level. The clipped portion of the histogram is modified to reduce the loss of image intensity value. Finally the clipped portion is redistributed uniformly to the entire dynamic range and the conventional histogram equalization is executed in each subhistogram independently. Based on the qualitative and the quantitative analysis, the QDAPLHE method outperforms some existing methods in literature.
ISSN:1024-123X
1563-5147
DOI:10.1155/2014/302732